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Neural Network Business Application
 
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I created this video with the YouTube Video Editor (http://www.youtube.com/editor)
Views: 1284 Visual Analytics
Neural Network & Its business applications (MGTC11-A1)
 
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A brief explaination of what Neural Network is, its application in business world, and its limitations. By: Team INFO( MGTC11 A1) Team Members: -Kai Ye -Patrick(WuHao) Pan -Anna Sun
Views: 6531 Kai Ye
Top 5 Uses of Neural Networks! (A.I.)
 
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Use my link http://www.audible.com/coldfusion or text coldfusion to 500-500 to get a free book and 30 day free trial. Subscribe here: https://goo.gl/9FS8uF Become a Patron!: https://www.patreon.com/ColdFusion_TV CF Bitcoin address: 13SjyCXPB9o3iN4LitYQ2wYKeqYTShPub8 Hi, welcome to ColdFusion (formerly known as ColdfusTion). Experience the cutting edge of the world around us in a fun relaxed atmosphere. Sources: Let there be Color: http://hi.cs.waseda.ac.jp/~iizuka/projects/colorization/en/ Pixel Enhancing CSI Style: https://arxiv.org/pdf/1702.00783.pdf?xtor=AL-32280680 Generating New Images: https://arxiv.org/pdf/1702.00783.pdf?xtor=AL-32280680 Pix2Pix demo: Image to image DEMO https://affinelayer.com/pixsrv/index.html Lip Reading: https://arxiv.org/abs/1611.01599 Creating a Scene From Scratch: https://arxiv.org/pdf/1612.00005.pdf //Soundtrack// **coming soon** » Google + | http://www.google.com/+coldfustion » Facebook | https://www.facebook.com/ColdFusionTV » My music | http://burnwater.bandcamp.com or » http://www.soundcloud.com/burnwater » https://www.patreon.com/ColdFusion_TV » Collection of music used in videos: https://www.youtube.com/watch?v=YOrJJKW31OA Producer: Dagogo Altraide » Twitter | @ColdFusion_TV
Views: 171378 ColdFusion
Neural Network in Two and Half Minutes
 
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A whiteboard animation on how Neural Networks work
How to make a neural network in your bedroom | Brittany Wenger |a TEDxCERN
 
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Brittany Wenger, 18, high school senior, brilliant young scientist and Grand Prize Winner 2012 Google Science Fair, for her project "Global Neural Network Cloud Service for Breast Cancer" talks about how she came to science in Research and Inspiration. In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 188981 TEDx Talks
Michael Alcorn | More Then Words : Business Applications of Recurrent Networks
 
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PyData Carolinas 2016 Recurrent neural networks have recently achieved spectacular results in many different natural language processing tasks, but their utility in more practical applications is largely undocumented. During this talk, you’ll learn about how Red Hat is leveraging the power of recurrent neural networks to make informed business decisions from sequential customer data. Recurrent neural networks have recently achieved spectacular results in many different natural language processing tasks, but their utility in more practical applications is largely undocumented. For companies that follow a subscription business model, sequential data can often be found in abundance, seemingly making recurrent neural networks a perfect fit for many prediction tasks. Unfortunately, resources describing how to leverage the power of recurrent neural networks in non-language settings are generally lacking. At Red Hat, we’re using recurrent neural networks to tackle a number of different business goals, including predicting customer churn and prioritizing support cases. During this talk, you’ll learn about Red Hat’s full deep learning pipeline, from data collection (e.g., mining website logs on Hadoop clusters and pulling data from SQL databases), to data preprocessing (e.g., dimensionality reduction in scikit-learn), to prediction. By the end, you’ll have the foundation necessary to begin implementing your own recurrent neural network solutions.
Views: 450 PyData
Machine Learning & Artificial Intelligence: Crash Course Computer Science #34
 
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So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever. Produced in collaboration with PBS Digital Studios: http://youtube.com/pbsdigitalstudios Want to know more about Carrie Anne? https://about.me/carrieannephilbin The Latest from PBS Digital Studios: https://www.youtube.com/playlist?list=PL1mtdjDVOoOqJzeaJAV15Tq0tZ1vKj7ZV Want to find Crash Course elsewhere on the internet? Facebook - https://www.facebook.com/YouTubeCrash... Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 377471 CrashCourse
Neural Networks, A Simple Explanation
 
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Oolution Technologies (a software company) presents a simple explanation about one type of Artificial Intelligence, Neural Networks. In particular Neural Networks are about computers simulating biological neurons and the way they process information. To keep it as simple as possible, this short animated video does not show how Neural Networks learn and it does not show an in depth explanation of the math behind Neural Networks. Instead it is meant to provide most people with an easy to understand format regarding the inner workings of Neural Networks and how they process inputs/information into outputs/results. To see Artificial Intelligence in action, please visit http://OolutionTech.com/Products.aspx?ref=youtube001 to try for free the ANNI program (ANNI is an acronym for Advanced Neural Network Investing), or the Dynamic Debt Annihilator program (which provides an optimal debt payoff strategy to eliminate debt the fastest way possible). Both of these programs use various Artificial Intelligence Technologies to provide a higher level of features and benefits to its users than other similar programs provide.
Views: 92286 Oolution Technologies
Neural Networks
 
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Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud262/l-315142919/m-432088650 Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud262 Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Views: 8158 Udacity
Neural Networks (Part 1)
 
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In this video, I present some applications of artificial neural networks and describe how such networks are typically structured. My hope is to create another video (soon) in which I describe how neural networks are actually trained from data.
Views: 20135 macheads101
Is Neural Network Really the Black Box? | Cypher 2017 | Machine Learning | AI | Great Learning
 
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#NeuralNetwork | Know more about our Business Analytics Program: http://bit.ly/2CvA1IQ Dr P K Viswanathan, Program Director- PGP-BABI at Great Lakes Institute of Management, unravels whether Neural Network is really a Black Box or is it just a White Box. Understand what the Black Box Conundrum is and what are its pros and cons. He also unfolds the black box conundrum with the help of multiple real-life problems. #GreatLearning #DeepLearning #MachineLearning #AI ------------------------------------------ Post Graduate Program in Business Analytics (PGP-BABI): The PGP-BABI offered by Great Lakes at Chennai, Gurgaon, Bangalore, Hyderabad, Mumbai and Pune cities is a 12 month blended (online + weekend classroom) program that covers a blend of business management skills and analytics capability with hands-on training on tools, real-life case studies that make candidates industry ready for business roles in analytics. Our PGP-BABI course has been ranked No.1 third time in a row by leading analytics site - Analytics India Magazine. The program is designed exclusively for working professionals ranging from young executives who wish to embark on managerial careers in analytics to senior industry leaders who wish to add analytics capabilities to grow their businesses. About Great Learning: Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U Do you know what the three pillars of Data Science? Here explaining all about thepillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: Google Plus: https://plus.google.com/u/0/108438615307549697541 Facebook: https://www.facebook.com/GreatLearningOfficial/ LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube
Views: 271 Great Learning
Biological Neural Network and Artificial Neural Network | Machine Learning Tutorial | Great Learning
 
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#BiologicalNeuralNetwork | Know more about our analytics programs: http://bit.ly/2lbPrud This machine learning tutorial helps you understand how Biological Neural Network (BNN) works and various characteristics of it. You will also learn how Artificial Neural Network (ANN) models mimics various characteristics of Biological Neural Network. #ArtificialNeuralNetwork #MachineLearningTutorial #ANN #BNN #MachineLearning -------------------------------------------------------------------------------------- PG Program in Business Analytics (PGP-BABI): 12-month program with classroom training on weekends + online learning covering analytics tools and techniques and their application in business. PG Program in Big Data Analytics (PGP-BDA): 12-month program with classroom training on weekends + online learning covering big data analytics tools and techniques, machine learning with hands-on exposure to big data tools such as Hadoop, Python, Spark, Pig etc. PGP-Data Science & Engineering: 6-month weekend and classroom program allowing participants enables participants in learning conceptual building of techniques and foundations required for analytics roles. PG Program in Cloud Computing: 6-month online program in Cloud Computing & Architecture for technology professionals who want their careers to be cloud-ready. Business Analytics Certificate Program (BACP): 6-month online data analytics certification enabling participants to gain in-depth and hands-on knowledge of analytical concepts. About Great Learning: Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube
Views: 85880 Great Learning
Artificial Neural Network Tutorial | Deep Learning With Neural Networks | Edureka
 
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( TensorFlow Training - https://www.edureka.co/ai-deep-learning-with-tensorflow ) This Edureka "Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you to understand the basics of Neural Networks and how to use it for deep learning. It explains Single layer and Multi layer Perceptron in detail. Below are the topics covered in this tutorial: 1. Why Neural Networks? 2. Motivation Behind Neural Networks 3. What is Neural Network? 4. Single Layer Percpetron 5. Multi Layer Perceptron 6. Use-Case 7. Applications of Neural Networks Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world. Please write back to us at [email protected] or call us at +91 88808 62004 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 56994 edureka!
9 Cool Deep Learning Applications | Two Minute Papers #35
 
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Machine learning provides us an incredible set of tools. If you have a difficult problem at hand, you don't need to hand craft an algorithm for it. It finds out by itself what is important about the problem and tries to solve it on its own. In this video, you'll see a number of incredible applications of different machine learning techniques (neural networks, deep learning, convolutional neural networks and more). Note: the fluid simulation paper is using regression forests, which is a machine learning technique, but not strictly deep learning. There are variants of it that are though (e.g., Deep Neural Decision Forests). ________________________ The paper "Toxicity Prediction using Deep Learning" and "Prediction of human population responses to toxic compounds by a collaborative competition" are available here: http://arxiv.org/pdf/1503.01445.pdf http://www.nature.com/nbt/journal/v33/n9/full/nbt.3299.html The paper "A Comparison of Algorithms and Humans For Mitosis Detection" is available here: http://people.idsia.ch/~juergen/deeplearningwinsMICCAIgrandchallenge.html http://people.idsia.ch/~ciresan/data/isbi2014.pdf Kaggle-related things: http://kaggle.com https://www.kaggle.com/c/dato-native http://blog.kaggle.com/2015/12/03/dato-winners-interview-1st-place-mad-professors/ The paper "Deep AutoRegressive Networks" is available here: http://arxiv.org/pdf/1310.8499v2.pdf https://www.youtube.com/watch?v=-yX1SYeDHbg&feature=youtu.be&t=2976 The furniture completion paper, "Data-driven Structural Priors for Shape Completion" is available here: http://cs.stanford.edu/~mhsung/projects/structure-completion Data-driven fluid simulations using regression forests: https://graphics.ethz.ch/~sobarbar/papers/Lad15/DatadrivenFluids.mov https://www.inf.ethz.ch/personal/ladickyl/fluid_sigasia15.pdf Selfies and convolutional neural networks: http://karpathy.github.io/2015/10/25/selfie/ Multiagent Cooperation and Competition with Deep Reinforcement Learning: http://arxiv.org/abs/1511.08779 https://www.youtube.com/watch?v=Gb9DprIgdGw&index=2&list=PLfLv_F3r0TwyaZPe50OOUx8tRf0HwdR_u https://github.com/NeuroCSUT/DeepMind-Atari-Deep-Q-Learner-2Player Kaggle automatic essay scoring contest: https://www.kaggle.com/c/asap-aes http://www.vikparuchuri.com/blog/on-the-automated-scoring-of-essays/ Great talks on Kaggle: https://www.youtube.com/watch?v=9Zag7uhjdYo https://www.youtube.com/watch?v=OKOlO9nIHUE https://www.youtube.com/watch?v=R9QxucPzicQ The thumbnail image was created by Barn Images - https://flic.kr/p/xxBc94 Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/
Views: 94006 Two Minute Papers
AI in Marketing
 
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Audience targeting and automatic content creation are just a few of the many ways AI can be used to help grow your user base and increase sales. In this video, i'll go over some startups that are applying AI to the marketing space and then programmatically walk through some AI techniques like matrix factorization, SVD, and LSTM neural networks that help a marketer outperform the competition and get the optimal results for their business. We've got quite a lot to cover in this video! Code for this video: https://github.com/llSourcell/AI_In_Marketing Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval More learning resources: https://www.youtube.com/watch?v=cdLUzrjnlr4 https://www.youtube.com/watch?v=BwmddtPFWtA https://www.thinkwithgoogle.com/marketing-resources/ai-personalized-marketing/ https://medium.com/the-mission/how-to-boost-your-marketing-with-artificial-intelligence-8c092d7e3f7d https://www.youtube.com/watch?v=9gBC9R-msAk Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 24602 Siraj Raval
Building Artificial Neural Network using R | Machine Learning Tutorial | Great Learning
 
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#ArtificialNeuralNetwork | This machine learning tutorial helps you build an Artificial Neural Network model using R with the help of a hands-on example. You will be understanding the application of Neural Networks in AI and solving business problems. Visit https://greatlearningforlife.com our learning portal for 100s of hours of similar free high-quality tutorial videos on Python, R, Machine Learning, AI and other similar topics Watch our new free Python for Data Science Beginners tutorial: https://greatlearningforlife.com/python Know more about our analytics programs: http://bit.ly/2zwfxNM #MachineLearningTutorial #MachineLearningWithR #GreatLearning -------------------------------------------------------------------------------------- PG Program in Business Analytics (PGP-BABI): 12-month program with classroom training on weekends + online learning covering analytics tools and techniques and their application in business. PG Program in Big Data Analytics (PGP-BDA): 12-month program with classroom training on weekends + online learning covering big data analytics tools and techniques, machine learning with hands-on exposure to big data tools such as Hadoop, Python, Spark, Pig etc. PGP-Data Science & Engineering: 6-month weekend and classroom program allowing participants enables participants in learning conceptual building of techniques and foundations required for analytics roles. PG Program in Cloud Computing: 6-month online program in Cloud Computing & Architecture for technology professionals who want their careers to be cloud-ready. Business Analytics Certificate Program (BACP): 6-month online data analytics certification enabling participants to gain in-depth and hands-on knowledge of analytical concepts. About Great Learning: Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about thepillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: Google Plus: https://plus.google.com/u/0/108438615307549697541 Facebook: https://www.facebook.com/GreatLearningOfficial/ LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube
Views: 88532 Great Learning
How Artificial Neural Network (ANN) Algorithm Work | Data Mining | Introduction to Neural Network
 
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#ArtificialNeuralNetwork | Beginners guide to how artificial neural network model works. Learn how neural network approaches the problem, why and how the process works in ANN, various ways errors can be used in creating machine learning models and ways to optimise the learning process. - Watch our new free Python for Data Science Beginners tutorial: https://greatlearningforlife.com/python - Visit https://greatlearningforlife.com our learning portal for 100s of hours of similar free high-quality tutorial videos on Python, R, Machine Learning, AI and other similar topics Know More about Great Lakes Analytics Programs: PG Program in Business Analytics (PGP-BABI): http://bit.ly/2f4ptdi PG Program in Big Data Analytics (PGP-BDA): http://bit.ly/2eT1Hgo Business Analytics Certificate Program: http://bit.ly/2wX42PD #ANN #MachineLearning #DataMining #NeuralNetwork About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/
Views: 66214 Great Learning
How do you use a neural network in your business?
 
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Ever wondered how you can integrate neural networks and artificial intelligence into your business? Scott Stephenson and Jeff Ward, aka, Susan tell you how to approach the subject. Visit https://www.deepgram.com/ to learn more about Deepgram.
Views: 37 Deepgram
How do Self-Organizing Maps Learn? (Part 1)
 
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http://ytwizard.com/r/VTXMyc http://ytwizard.com/r/VTXMyc Deep Learning A-Z™: Hands-On Artificial Neural Networks Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.
Views: 16418 business & marketing
Understanding evolution with neural networks using Pixling
 
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Sponsored by: Coursera.org, thanks! Get the world's best online education experience on subjects such as Data Science, Business, Blockchain, you name it at Coursera.org http://go.thoughtleaders.io/721220181119 🔗 Fun Fun Forum topic dedicated to this episode [ Forum Patrons only ] https://www.funfunforum.com/t/understanding-evolution-with-neural-networks-using-pixling/6442 🔗 The world from the episode on pixling.world https://pixling.world/1sv51RzODhKvfAveBjrHp0 🔗 Fredrik Norén on Twitter https://twitter.com/jfnoren 🔗 mpj on Twitter https://twitter.com/mpjme 🔗 Help translate the show to your language http://www.youtube.com/timedtext_cs_panel?tab=2&c=UCO1cgjhGzsSYb1rsB4bFe4Q Me and my old time friend Fredrik Norén take a look at his project pixling.world, which is an AI sandbox with neural network agents that you can use to understand the process of evolution. Built in TypeScript and WebGL, pixling.world is quite an interesting animal-
Views: 5987 Fun Fun Function
Machine Learning with TensorFlow for Business Intelligence : Introduction to neural networks
 
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http://ytwizard.com/r/hghLz5 http://ytwizard.com/r/hghLz5 Machine Learning with TensorFlow for Business Intelligence Leverage Machine Learning and TensorFlow in Python to improve your business! Build deep learning algorithms from scratch
Views: 42 Smart Media
Neural Networks For Recommender Systems
 
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Recommender Systems are arguably the most common business application of Machine Learning systems. Recently a new blend of recommender systems have been developed by leveraging the tools and the modeling flexibility from the Deep Learning ecosystem. This presentation gives an overview of the main RecSys concepts such as matrix completion for collaborative filtering and relate those to current trends in Neural Network architectures. EVENT: dotAI 2017 SPEAKER: Olivier Grisel PERMISSIONS: The original video was published on dotconferences YouTube channel with the Creative Commons Attribution license (reuse allowed). ORIGINAL SOURCE: https://www.youtube.com/watch?v=HG3FDCegKVc&t=8s
Views: 5936 Coding Tech
Real Life Applications of Neural Networks
 
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Neural Network is "a computer system modelled on the human brain and nervous system". But we are not going to teach that, we are showing you that, how important they are. As some big giants are using them in their applications.
Views: 252 Intelligent Tech
Lecture 6 Business Data Mining (Artificial Neural Network and Support Vector Machine)
 
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Lecture 6 Business Data Mining (Artificial Neural Network and Support Vector Machine)
Views: 84 Phayung Meesad
What is Neural Network - Decoded in 60 Seconds | A Brief Introduction to Neural Networks | ACADGILD
 
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Neural Network Decoded in 60 Seconds | What is Neural Network | Introduction to Neural Networks https://acadgild.com/big-data/data-science-training-certification?aff_id=6003&source=youtube&account=youtube&campaign=EGzZzS3e620-neural-networks-decoded&utm_medium=youtub&utm_source=youtube&utm_campaign=EGzZzS3e620-neural-networks-decoded What is Neural Network? A neural network is a series of algorithms that attempt to identify underlying relationships in a set of data by using a process that is similar to the way the human brain works. Why Neural Network? Neural networks have the ability to adapt to changing input. So, it can provide the best possible results without the need to redesign the output criteria. How does a Neural Network operate? A neural network operates similar to the brain’s neural network. A “neuron” in the network is a simple mathematical function capturing and organizing information according to an architecture. The network closely resembles statistical methods such as curve fitting and regression analysis. Neural network is basically a “connectionist” computational system. The computational systems we write are procedural; a program starts at the first line of code, executes it, and goes on to the next, following instructions in a linear fashion. A true neural network does not follow a linear path. Rather, information is processed collectively, parallelly throughout a network of nodes or Neurons. Application of Neural Networks: Neural networks are widely used in financial operations, enterprise planning, trading, business analytics and product maintenance. Neural networks are common in business applications such as forecasting and marketing research solutions, fraud detection and risk assessment. Please subscribe the channel for more updates on the latest technical skills and tutorials. #AI, #Deeplearning, #machinelearning, #Neuralnetwork, #artificialinteligence, #Datascience, For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 331 ACADGILD
Neural networks by example - Natalia An & Katya Mustafina
 
54:27
In the last 5 years we observe rapidly increasing interest to artificial neural networks. But what are neural networks and how do they differ from conventional algorithms? What kind of problems we can resolve with neural networks that could not solve with traditional approaches? In this session we will answer those questions explaining neural networks principles. We will explain concepts behind neural networks and give insight of neural networks usage such as self-driving cars, image recognition, automated translation and text analysis. We will walk you through real life application example: recognition of hand written digits using classical MNIST dataset and convolutional neural network. As a framework Microsoft CNTK and Tensorflow will be used in practical part of presentation. NDC Conferences https://ndc-london.com https://ndcconferences.com
Views: 921 NDC Conferences
12a: Neural Nets
 
50:43
*NOTE: These videos were recorded in Fall 2015 to update the Neural Nets portion of the class. MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this video, Prof. Winston introduces neural nets and back propagation. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 249387 MIT OpenCourseWare
Restricted Boltzmann Machine | Neural Network Tutorial | Deep Learning Tutorial | Edureka
 
12:12
** AI & Deep Learning with Tensorflow Training: https://www.edureka.co/ai-deep-learning-with-tensorflow ** This Edureka video on "Restricted Boltzmann Machine" will provide you with a detailed and comprehensive knowledge of Restricted Boltzmann Machines, also known as RBM. You will also get to know about the layers in RBM and their working. This video covers the following topics: 1. History of RBM 2. Difference between RBM & Autoencoders 3. Introduction to RBMs 4. Energy-Based Model & Probabilistic Model 5. Training of RBMs 6. Example: Collaborative Filtering - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE #RBM #RestrictedBoltzmannMachine #NeuralNetworks #DeepLearning #Autoencoders #DimensionalityReduction #CollaborativeFiltering - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world. ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For AI & Deep Learning with TensorFlow, call us at US: +18336900808 (Toll Free) or India: +918861301699 Or, write back to us at [email protected]
Views: 2031 edureka!
Deep Learning A-Z™: Hands-On Artificial Neural Networks : Restricted Boltzmann Machine
 
17:30
http://ytwizard.com/r/VTXMyc http://ytwizard.com/r/VTXMyc Deep Learning A-Z™: Hands-On Artificial Neural Networks Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.
AETROS TRAINER Sneak Peek - Artificial Neural Network builder&trainer
 
01:39
Newest version: https://www.youtube.com/watch?v=qS8qhzXRQWE More information at: http://aetros.com/trainer - open beta registration open Supercharge your business with artificial intelligence. Build, train, monitor, and deploy artificial neural network using a web application. Machine learning made easy. Register for free in our open beta at http://aetros.com/
Views: 1750 AETROS
Neural Networks: Part I
 
25:00
Modeling complex input-outcome relationships; Network architecture: layers and nodes; Neural nets and regression models; Training the network; Avoiding over-fitting This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: http://www.dataminingbook.com https://www.twitter.com/gshmueli https://www.facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Networks: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 746 Galit Shmueli
Deep Learning: Intelligence from Big Data
 
01:24:17
Deep Learning: Intelligence from Big Data Tue Sep 16, 2014 6:00 pm - 8:30 pm Stanford Graduate School of Business Knight Management Center – Cemex Auditorium 641 Knight Way, Stanford, CA A machine learning approach inspired by the human brain, Deep Learning is taking many industries by storm. Empowered by the latest generation of commodity computing, Deep Learning begins to derive significant value from Big Data. It has already radically improved the computer’s ability to recognize speech and identify objects in images, two fundamental hallmarks of human intelligence. Industry giants such as Google, Facebook, and Baidu have acquired most of the dominant players in this space to improve their product offerings. At the same time, startup entrepreneurs are creating a new paradigm, Intelligence as a Service, by providing APIs that democratize access to Deep Learning algorithms. Join us on September 16, 2014 to learn more about this exciting new technology and be introduced to some of the new application domains, the business models, and the key players in this emerging field. Moderator Steve Jurvetson, Partner, DFJ Ventures Panelists Adam Berenzweig, Co-founder and CTO, Clarifai Naveen Rao, Co-founder and CEO, Nervana Systems Elliot Turner, Founder and CEO, AlchemyAPI Ilya Sutskever, Research Scientist, Google Brain Demo Companies**: Clarifai | SkyMind | Ersatz Labs | AlchemyAPI ** Follow (@VLAB) on Twitter and Event Hashtag #VLABdl
Views: 543806 vlabvideos
Convolutional Neural Network (CNN) | Convolutional Neural Networks With TensorFlow | Edureka
 
22:14
( TensorFlow Training - https://www.edureka.co/ai-deep-learning-with-tensorflow ) This Edureka "Convolutional Neural Network Tutorial" video (Blog: https://goo.gl/4zxMfU) will help you in understanding what is Convolutional Neural Network and how it works. It also includes a use-case, in which we will be creating a classifier using TensorFlow. Below are the topics covered in this tutorial: 1. How a Computer Reads an Image? 2. Why can't we use Fully Connected Networks for Image Recognition? 3. What is Convolutional Neural Network? 4. How Convolutional Neural Networks Work? 5. Use-Case (dog and cat classifier) Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. Machine learning is one of the fastest-growing and most exciting fields out there, and Deep Learning represents its true bleeding edge. Deep learning is primarily a study of multi-layered neural networks, spanning over a vast range of model architectures. Traditional neural networks relied on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kinds of nets are capable of discovering hidden structures within unlabeled and unstructured data (i.e. images, sound, and text), which constitutes the vast majority of data in the world. Please write back to us at [email protected] or call us at +91 88808 62004 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 55121 edureka!
OKC Big Data: Paul Bruffett - Deep Learning with Artificial Neural Networks [2017]
 
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A Technical Introduction to Deep Learning with Artificial Neural Networks. This talk will provide a quick overview to the key theoretical concepts that underpin modern neural networks and the business problems they solve. Then we will discuss some of the main architectures for neural networks, the frameworks with a focus on TensorFlow and Keras and the challenges to being successful with deep learning. Bio: With a bachelor's in English Literature, MBA and MS in MIS, all from the University of Oklahoma, Paul Bruffett continues to teach graduate classes in Big Data and Python development at the OU as an adjunct professor. Passionate about new technologies and systems design, Paul currently focuses on supporting Devon Energy's advanced analytics initiatives. -- Watch live at https://www.twitch.tv/techlahoma
Views: 39 Techlahoma
R-Session 11 - Statistical Learning - Neural Networks
 
29:05
Source: neuralnet: Training of Neural Network by Frauke Gunther and Stefan Fritsch - The R Journal Vol. 2/1, June 2010
Views: 79300 Hamed Hasheminia
Convolution Neural Network (CNN): Concept and Application
 
04:31
Learnin28day.com is an initiative to educate beginners with new digital technology concepts with examples from real life business cases. Convolution Neural Network (CNN) is an important concept in Machine Learning.
Views: 37 Learnin28days
AI in Medicine | Drug Discovery with GANs (TensorFlow Tutorial)
 
22:38
How do we use AI to cure drug discovery? This is apart of my AI for business series right here on Youtube. Subscribe to stay up to date! In this video I'm going to cover how the drug discovery process works in clinical labs and how AI can be used to speed up that process by orders of magnitude. We'll look at 3 different papers that used different types of neural networks, and the last one is what we'll focus on; the General Adversarial Network. Code for this video: https://github.com/llSourcell/AI_for_healthcare Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Curriculum: https://github.com/llSourcell/AI_For_Business_Curriculum More learning resources: https://github.com/plotly/dash-drug-discovery-demo https://www.youtube.com/watch?v=FTr3n7uBIuE&t=25s https://www.youtube.com/watch?v=yz6dNf7X7SA https://www.youtube.com/watch?v=Sw9r8CL98N0 http://www.healthcareitnews.com/slideshow/how-ai-transforming-healthcare-and-solving-problems-2017 Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ Sign up for the next course at The School of AI: https://www.theschool.ai And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w
Views: 35020 Siraj Raval
Ethics In AI And Artificial Narrow Intelligence | AI for Business #5
 
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Ethics In AI And Artificial Narrow Intelligence | AI for Business #5 In this episode of AI for Business, we dive into the complex issues surrounding ethics in AI and artificial narrow intelligence. You can download the AI ethics code here: https://grow.ac/aiethics Bernardo is back, and this time he’s going to take us through the top 5 most discussed ethical concerns of artificial narrow intelligence: 1) Interpretability 2) Data Citizenship 3) Fairness 4) Governance 5) The Future of Work Understanding ethics in AI is a lot more complicated than “will robots take over the world?”. It’s now crucial for businesses to follow research areas such as interpretability (or ‘explainable’ AI) as customers become more concerned and curious about how their data is being used, and since the GDPR came into effect in May 2018. From collaborative filtering to convolutional neural networks, customers often encounter a frustrating lack of transparency around machine learning and automated decision-making. - How exactly are decisions about credit ratings made? - How does image recognition work? - Are deep neural networks just too complicated to be ethical? - Should Netflix, Spotify and Facebook provide customers with more algorithm transparency and make AI more interpretable? - How did Netflix know you’d like to start binge-watching Queer Eye? (It’s because you watched 9 seasons of Drag Race in just 3 weeks.) Do you think we covered the key concerns surrounding ethics in AI and artificial narrow intelligence? What did we miss? Let us know in the comments. Get your free downloadable AI ethics code here: https://grow.ac/aiethics ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/school/growt... Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Video URL: https://youtu.be/MEiosP87aJM
Views: 861 Growth Tribe
Intro to Graph Convolutional Networks
 
47:45
Graham Ganssle, Data Science Lead at Expero, gave this introduction to Graph Convolutional Networks at a recent meetup of Austin Data Geeks / Austin AI. http://austindatageeks.org https://www.experoinc.com/author/graham-ganssle Abstract Is this group of delis a money laundering ring, or are they simply exchanging provolone? Why does Devin have so many Facebook friends, and I only have a handful? The answer to one of these questions is obvious (because I’m a nerd giving an ML presentation), but both can be solved with graph convolutional networks. GCNs use a novel neural network kernelization which generalizes the accuracy and speed of CNNs to non-Euclidean information spaces. About the Speaker Graham Ganssle loves data. His favorite part of work at Expero is daydreaming up innovative solutions to quantifiable problems and planning an implementation strategy. Building intelligent systems is his passion whether it’s automated derivatives trading bots, adaptive image processing algorithms, or autonomous musical composers. Whether deep learning is the optimal solution or not, helping customers succeed through solving their analytics problems is where Graham finds the most satisfaction. Graham Ganssle’s physics Ph.D. focused on digital signal processing, specifically on a (then) new optimization method which used naturally coupled wavefields to stabilize convergence. He also holds a masters degree in applied physics and a professional geoscientist license. Graham worked in the oil and gas vertical for ten years, performing data science and quantitative geophysics for clients around the world. He has numerous publications on a variety of scientific topics and has been awarded both scientific and business achievement awards.
Views: 5390 Global Data Geeks
Speed Sign Recognition by Convolutional Neural Networks
 
02:00
This video show a Speed Sign Detection and Recognition vision application that is uses a Convolutional Neural Network. This application is fully trainable by a set of example images. Instead of using algorithm complexity we used training data to improve recognition reliability. The algorithm has a very parallel nature and thereby scales very well on the current popular CUDA enabled Grapics Processors from Nvidia. We mapped the algorithm to a Nvidia Geforce GTX 460. The GPU implementation can perfome realtime processing of 35 fps on a 720x1280 HD video stream. More invormation can be found on our website: http://parse.ele.tue.nl/research/projects
Views: 6395 Maurice Peemen
Joe Jevnik - A Worked Example of Using Neural Networks for Time Series Prediction
 
35:19
PyData New York City 2017 Slides: https://github.com/llllllllll/osu-talk Most neural network examples and tutorials use fake data or present poorly performing models. In this talk, we will walk through the process of implementing a real model, starting from the beginning with data collection and cleaning. We will cover topics like feature selection, window normalization, and feature scaling. We will also present development tips for testing and deploying models.
Views: 10629 PyData
Neural Networks in Practice
 
06:48
How neural networks were introduced in real business in Russia
Views: 37 Sergey Tolkachev
Building Smart Java Applications with Neural Networks, Using the Neuroph Framework
 
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Artificial neural networks provide solutions for ill-defined problems including recognition, such as image, character, and gesture; forecasting, such as stock market prediction; and optimization, such as JVM parameters. This session introduces the Neuroph Java open source neural network framework and shows how to use it, via demos and code samples. The session is intended for developers interested in artificial intelligence and the problems outlined above. You can learn more at: http://neuroph.sourceforge.net/ You will learn about • The Java neural network framework Neuroph and its features and development • Solving problems by using neural networks • Using neural networks for image recognition, stock market prediction, and JVM tweaking • Why and how Neuroph moved to the NetBeans platform and the resulting gains Copyright © 2013 Oracle and/or its affiliates. Oracle® is a registered trademark of Oracle and/or its affiliates. All rights reserved. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the "Materials"). The Materials are provided "as is" without any warranty of any kind, either express or implied, including without limitation warranties of merchantability, fitness for a particular purpose, and non-infringement.
Copy of Lecture 6 Business Data Mining (Artificial Neural Network and Support Vector Machine)
 
51:48
Lecture 6 Business Data Mining (Artificial Neural Network and Support Vector Machine)
Views: 39 Phayung Meesad

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