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The Ultimate Introduction to Web Scraping and Browser Automation
 
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Whenever you need to import data from an external website, hopefully they provide an API and make your life easy. But in the real world, that's not always the case. There are numerous reasons why you might want to get data from a web page or multiple web pages, and there's no API in sight, and in that case you're going to need to fall back onto Web Scraping and Browser Automation. In this screencast I'm going to give a high level overview of how to scrape websites, then cover five different scenarios, in increasing difficulty, for practical web scraping. There is a massive amount of information in this screencast and I'm going to straight up bombard you with it, but if you can make it until the end I guarantee you will come out knowing how to scrape websites with the best of them. As always, you can hit me up on twitter @AlwaysBCoding with questions, comments, to argue about programming, or to drop a suggestion for which topics I should cover next.
Views: 143657 Decypher Media
Automate Social - Grab Social Data with Python - Part 1
 
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Coding with Python - Automate Social - Grab Social Data with Python - Part 1 Coding for Python is a series of videos designed to help you better understand how to use python. In this video we discover a API that will help us grab social data (twitter, facebook, linkedin) using just a person's email address. API - FullContact.com Django is awesome and very simple to get started. Step-by-step tutorials are to help you understand the workflow, get you started doing something real, then it is our goal to have you asking questions... "Why did I do X?" or "How would I do Y?" These are questions you wouldn't know to ask otherwise. Questions, after all, lead to answers. View all my videos: http://bit.ly/1a4Ienh Get Free Stuff with our Newsletter: http://eepurl.com/NmMcr The Coding For Entrepreneurs newsletter and get free deals on premium Django tutorial classes, coding for entrepreneurs courses, web hosting, marketing, and more. Oh yeah, it's free: A few ways to learn: Coding For Entrepreneurs: https://codingforentrepreneurs.com (includes free projects and free setup guides. All premium content is just $25/mo). Includes implementing Twitter Bootstrap 3, Stripe.com, django south, pip, django registration, virtual environments, deployment, basic jquery, ajax, and much more. On Udemy: Bestselling Udemy Coding for Entrepreneurs Course: https://www.udemy.com/coding-for-entrepreneurs/?couponCode=youtubecfe49 (reg $99, this link $49) MatchMaker and Geolocator Course: https://www.udemy.com/coding-for-entrepreneurs-matchmaker-geolocator/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Marketplace & Dail Deals Course: https://www.udemy.com/coding-for-entrepreneurs-marketplace-daily-deals/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Free Udemy Course (40k+ students): https://www.udemy.com/coding-for-entrepreneurs-basic/ Fun Fact! This Course was Funded on Kickstarter: http://www.kickstarter.com/projects/jmitchel3/coding-for-entrepreneurs
Views: 45553 CodingEntrepreneurs
Automated data scraping from websites into Excel
 
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Our Excel training videos on YouTube cover formulas, functions and VBA. Useful for beginners as well as advanced learners. New upload every Thursday. For details you can visit our website: http://www.familycomputerclub.com You can scrape, pull or get data from websites into Excel by performing a few simple steps. 1. record a macro to find out how one or many tables or data can be scraped from the website 2. Study the code carefully 3. Create an Excel sheet containing the links that get you the data from the appropriate web pages 4. Automate the process using a loop that creates a) New worksheets b) Automatically changes the link to the web pages that have the required data You can view the complete Excel VBA code here: http://www.familycomputerclub.com/scrpae-pull-data-from-websites-into-excel.html http://www.familycomputerclub.com/get-web-page-data-int-excel-using-vba.html Interesting Links: http://www.tushar-mehta.com/publish_train/xl_vba_cases/vba_web_pages_services/index.htm Get the book Excel 2016 Power Programming with VBA: http://amzn.to/2kDP35V If you are from India you can get this book here: http://amzn.to/2jzJGqU
Views: 499869 Dinesh Kumar Takyar
Automate Data Extraction – Web Scraping, Screen Scraping, Data Mining
 
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Extract data from unstructured sources with Automate. Learn more: https://www.helpsystems.com/product-lines/automate/data-scraping-extraction Modern businesses run on data. However, if the source of the data is unstructured, extracting what you need can be labor-intensive. For example, you may want to pull information from the body of incoming emails, which have no pre-determined structure. Especially important for today’s enterprises is gleaning data from the web. Using traditional methods, website data extraction can involve creating custom processing and filtering algorithms for each site. Then you might need additional scripts or a separate tool to integrate the scraped data with the rest of your IT infrastructure. Your busy employees don’t have time for that. Any company that handles a high volume of data needs a comprehensive automation tool to bridge the gap between unstructured data and business applications. Automate’s sophisticated data extraction, transformation, and transport tools keep your critical data moving without the need for tedious manual tasks or custom script writing. Learn more: https://www.helpsystems.com/product-lines/automate/data-scraping-extraction
Views: 2236 HelpSystems
YOW! Data 2016 Natalia Rümmele - Automating Data Integration with Machine Learning
 
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The world of data is a messy and unstructured place, making it difficult to gain value from data. Things get worse when the data resides in different sources or systems. Before we can perform any analytics in such a case, we need to combine the sources and build a unified view of the data. To handle this situation, a data scientist would typically go through each data source, identify which data is of interest, and define transformations and mappings which unify these data with other sources. This process usually includes writing lots of scripts with potentially overlapping code – a real headache in the everyday life of a data scientist! In this talk we will discuss how machine learning techniques and semantic modelling can be applied to automate the data integration process. Natalia is a data scientist in the data platforms group at Data61, CSIRO. She is passionate about social network analysis, web mining and machine learning with specialization on data mining and link prediction. Her experience includes working on data intensive projects in Ukraine, Austria, Japan and Australia. For more on YOW! Data, visit http://data.yowconference.com.au
Views: 654 YOW! Conferences
WHY?? - A MINING WiFi Router???
 
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Sign up for Private Internet Access VPN at https://www.privateinternetaccess.com/pages/linus-tech-tips/linus2 Check out the Thermaltake Level 20 series cases on Amazon at http://geni.us/RKaBH4V We find out why on Earth the Bitmain AntRouter exists... Buy actual routers: On Amazon: http://geni.us/pew8K On Newegg: http://geni.us/5YYQ Discuss on the forum: https://linustechtips.com/main/topic/981171-why-bitmain-antrouter/ Our Affiliates, Referral Programs, and Sponsors: https://linustechtips.com/main/topic/75969-linus-tech-tips-affiliates-referral-programs-and-sponsors Get Private Internet Access today at http://geni.us/7lLuafK Linus Tech Tips merchandise at http://www.designbyhumans.com/shop/LinusTechTips/ Linus Tech Tips posters at http://crowdmade.com/linustechtips Our Test Benches on Amazon: https://www.amazon.com/shop/linustechtips Our production gear: http://geni.us/cvOS Twitter - https://twitter.com/linustech Facebook - http://www.facebook.com/LinusTech Instagram - https://www.instagram.com/linustech Twitch - https://www.twitch.tv/linustech Intro Screen Music Credit: Title: Laszlo - Supernova Video Link: https://www.youtube.com/watch?v=PKfxmFU3lWY iTunes Download Link: https://itunes.apple.com/us/album/supernova/id936805712 Artist Link: https://soundcloud.com/laszlomusic Outro Screen Music Credit: Approaching Nirvana - Sugar High http://www.youtube.com/approachingnirvana Sound effects provided by http://www.freesfx.co.uk/sfx/
Views: 771817 Linus Tech Tips
PDF Data Extraction and Automation 3.1
 
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Learn how to read and extract PDF data. Whether in native text format or scanned images, UiPath allows you to navigate, identify and use PDF data however you need. Read PDF. Read PDF with OCR.
Views: 97684 UiPath
Automating Data Calculations and Analysis Using Do While Loop Macro
 
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If you wish to automate data calculations and analysis you can use a 'do while' loop macro. Of course, you can do multiple things like copying and pasting in another worksheet in the looping process. You use the do while loop when you know the starting point but are not sure of the last data entry point. Therefore you need to define a starting point, a condition that must be met for the loop to perform its job and an increment in the value of the initialized point or starting point like a row or column value. Looping processes are important for any kind of automation. Another looping form is the 'for next' loop that works very efficiently if you know the starting and end points like for example at which row you wish to start the calculations and which row you wish to end the process.
Views: 60190 Dinesh Kumar Takyar
The ABB digital mine
 
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Mines are an essential part of modern economies, providing the raw materials needed for the technology that powers the modern world. However, miners often put their lives at risk, travelling deep underground in dangerous conditions to bring these precious elements to the surface. ABB has a comprehensive portfolio of products and solutions – including ABB Ability, our suite of digital solutions – that are transforming the way mines operate, creating a digitally-enabled environment that is safe, clean and sustainable, with a workforce carrying out exciting, stimulating tasks. Welcome to the ABB Digital Mine. For more, see www.abb.com/mining
Views: 8074 ABB
How To Automate Facebook Login With Python
 
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Awesome to have you here ❤️ TIME TO CODE 🖥️ 🎧 ——————————————————————————————————————————————— JOIN THE DEVELOPER COMMUNITY 👬: ——————————————————————————————————————————————— 📺 SUBSCRIBE ON YOUTUBE: https://goo.gl/qkgzWg 👥 JOIN US ON SLACK: https://goo.gl/dbpgZR 💌 JOIN MY EXCLUSIVE MAILING LIST: https://goo.gl/qz1xeZ ——————————————————————————————————————————————— HOW TO ASK ME QUESTIONS 🎤: ——————————————————————————————————————————————— 👬 1:1 PRIVATE MENTORSHIP: https://goo.gl/P3PgC2 🎨 DM ME ON INSTAGRAM: https://www.instagram.com/jgordonfisher 👥 ASK ME ON SLACK: https://goo.gl/dbpgZR 🔗 Linkedin: https://www.linkedin.com/in/johngordonfisher/ 💬 Facebook: https://www.facebook.com/jgfishercode/ 🐤 Twitter: https://twitter.com/jgordonfisher 🖍️ Quora: https://www.quora.com/profile/John-Fisher-167 ——————————————————————————————————————————————— MORE ABOUT WHAT YOU WATCHED 🎥: ——————————————————————————————————————————————— 📜 DESCRIPTION: How To Automate Facebook Login With Python using the Selenium package. If you guys run into any issues let me know! Automating things with the browser can be a little tricky because of the moving parts, happy to help you guys out and work through any problems. ChromeDriver: https://chromedriver.storage.googleapis.com/index.html?path=2.38/ 👨‍💻 CODE: https://github.com/jg-fisher/autoFB ——————————————————————————————————————————————— BOOKS I LOVE ❤️: ——————————————————————————————————————————————— DEEP LEARNING: https://amzn.to/2LomU4y HANDS-ON MACHINE LEARNING: https://amzn.to/2JSxhIv VIOLENT PYTHON: https://amzn.to/2u02rZf BLACK-HAT PYTHON: https://amzn.to/2u02rZf
Views: 2377 John G. Fisher
Automate Web Data Extraction - UiPath Studio
 
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Web scraping is a very tedious task for most website owners and developers. In this video, we'll discuss how to use UiPath in automating data extraction from a website. Using these steps, we can scrape data out of multiple web pages in few minutes by making just a few simple steps to define web extraction patterns. To find out more about UiPath or to request a free trial, please contact us: http://www.uipath.com/contact-us.
Views: 55869 UiPath
How To Automate Any Website Process Using Mozenda To Mimic Human Behavior
 
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Mozenda web automation replicates human processes, from mouse clicks and page scrolls, to form entry and even shopping cart purchasing.
Views: 418 MozendaSupport
Web Page Crawling - VBA Automation
 
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In this video you will learn 2 things - 1) How to log in to any webpage using excel/vba 2) How to extract data from any web page
Enterprise Connectors - Social Media Data Mining
 
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This is a replay of the webinar covering using the CData Enterprise Connectors for FireDAC to connect to Twitter and Facebook to mine social media data. The examples are in Delphi, but they could also easily be adaptable for C++Builder too.
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 145519 APMonitor.com
Learning Data Mining with R : Market Basket Analysis | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2lXhDAx]. The aim of this video is to show a little example to motivate the attendee based on the standard market basket analysis. • Load and parse transaction data • Calculate measures on the data • Generate and inspect association rules For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 591 Packt Video
Spatial Data Mining I: Essentials of Cluster Analysis
 
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Whenever we look at a map, it is natural for us to organize, group, differentiate, and cluster what we see to help us make better sense of it. This session will explore the powerful Spatial Statistics techniques designed to do just that: Hot Spot Analysis and Cluster and Outlier Analysis. We will demonstrate how these techniques work and how they can be used to identify significant patterns in our data. We will explore the different questions that each tool can answer, best practices for running the tools, and strategies for interpreting and sharing results. This comprehensive introduction to cluster analysis will prepare you with the knowledge necessary to turn your spatial data into useful information for better decision making.
Views: 17455 Esri Events
Packet Hacking Village 2017 - YALDA - LARGE SCALE DATA MINING FOR THREAT INTELLIGENCE - GITA ZIABARI
 
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YALDA - LARGE SCALE DATA MINING FOR THREAT INTELLIGENCE GITA ZIABARI, SENIOR THREAT RESEARCH ENGINEER AT FIDELIS CYBERSECURITY PRESENTATION SLIDES: PHV2017-GZIABARI.PDF SLIDES AVAILABLE ON: https://www.wallofsheep.com Every SOC is deluged by massive amounts of logs, suspect files, alerts and data that make it impossible to respond to everything. It is essential to find the signal in the noise to be able to best protect an organization. This talk will cover techniques to automate the processing of data mining malware to derive key indicators to find active threats against an enterprise. Techniques will be discussed covering how to tune the automation to avoid false positives and the many struggles we have had in creating appropriate whitelists. We'll also discuss techniques for organizations to find and process intelligence for attacks targeting them specifically that no vendor can sell or provide them. Audiences would also learn about method of automatically identifying malicious data submitted to a malware analysis sandbox. Gita Ziabari (Twitter: @gitaziabari) is working at Fidelis Cybersecurity as a Senior Threat Research Engineer. She has more than 13 years of experience in threat research, networking, testing and building automated frameworks. Her expertise is writing automated tools for data mining. She has unique approaches and techniques in automation. Brought to you by Aries Security - https://www.ariessecurity.com
Views: 110 Wall of Sheep
How to Automate Prospecting and Target List Building on LinkedIn With DMS Capture
 
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For more information - visit www.ringlead.com/contact-us RingLead’s end-to-end data management solution DMS features a key discovery and prospecting tool, DMS Capture, that automates target list building, enabling any sales rep, recruiter or marketer to instantly generate targeted lead lists complete with enriched fields, so your organization can manage their data... faster, and smarter. Sales reps understand that calling and nurturing leads these targeted lead list is indispensable to their account-based marketing strategy - it’s how they generate drive their organizations revenue. However, the average rep only spends 30 percent of their day selling - the rest of their time is often spent researching data on Google, LinkedIn and other social sites to build lead list and to find key information on their target leads and accounts. The all-too-common trade-off between selling and prospecting that damages most businesses does not need to exist at your organization. RingLead DMS Capture is used by thousands of sales reps, recruiters, and marketers to compliment existing tools like LinkedIn, Google Searches, and Company Webpages to automate prospecting. DMS Capture recognizes data patterns from countless origins, enabling reps to click Capture and instantly generate lead lists of 1,000+, all with enriched data fields like direct dials, validated email addresses, job titles, and more. Your rep then imports that list to Salesforce where DMS prevents any duplicates from entering your Salesforce, enables you to add leads to existing accounts, and standardizes your new data to ensure the quality of your database remains intact. Creating and maintaining a clean, dupe-free and enriched database has never been simpler.
Views: 324 RingLead
QIWare - One Click Data Mining
 
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Explainer video for the "Quick Insights Ware", an innovative data mining solution, that cuts time and costs in building business-driven analytics models such as customer segmentation, churn prediction and next best activity. QIWare by Forte Wares is a rapid analytics solution that unites the power of ETL with data mining. Designed with the adaptability to suit companies in a broad range of industries, QIWare expedites and simplifies the process of preparing data for analysis. Automating the end-to-end process, QIWare further delivers interactive, agile tools to help users when mining prepared data. BENEFITS • Cost-efficient, all-in-one analytics solution • Increased efficiency and business relevance when building analytical models • Drastically reduced data preparation time for modeling • Mitigated chance of human error FEATURES • Business-driven model development paradigm • Fully integrated and searchable data and model dictionaries • Improved data organization using a systematized task-oriented approach • In-DB processes and DB-based performance & scalability • Automated dependency tracking from data sources to model scores
Views: 448 Forte Wares
Sensor solutions for Mobile Automation | SICK AG
 
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For more information, please visit: http://sick.com/mobile-applications ----------------------------------------------------------------------------------- Efficiency in motion - Automation goes mobile Processes are becoming more efficient, more precise, and more environmentally friendly - even with mobile machines. Take advantage of our knowledge and experience in factory and logistics automation now: We offer driver assistance, environmental detection, positioning and telematic data handling. And innovative solutions - designed for machine manufacturers. ----------------------------------------------------------------------------------- Subscribe to our YouTube channel and watch all videos from SICK: http://www.youtube.com/subscription_center?add_user=sicksensors Follow us: Facebook: https://www.facebook.com/SICK.Deutschland Twitter: https://twitter.com/sick_de Google+: https://plus.google.com/105985015069795775228 LinkedIn: https://www.linkedin.com/company/sick-ag For information and general inquiries please contact: http://www.sick.com/contact
YouTube Data API - Data Mining #2
 
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Data mining YouTube using youtube.search.list and youtube.videos.list to forecast the senate races of 2014. And quantifying our probability using 2012 senate races data and stats from YouTube during the same period. Github/NBViewer Link: http://nbviewer.ipython.org/github/twistedhardware/mltutorial/blob/master/notebooks/data-mining/2.%20YouTube%20Data.ipynb
Views: 6120 Roshan
Webinar - Automating App Retention & Engagement
 
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Machine Learning & Artificial Intelligence driven Growth Marketing & Personalization.
Views: 1294 Pyze
Best Data Mining, Web Scraping and ebay Template Services
 
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www.datatudetechnologies.com/ - We provide data mining, eBay templates, web scraping, data extraction, web automation, Amazon automation, eBay automation services to our clients around the globe.
Best Data Mining, Web Scraping and ebay Template Services
 
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www.datatudetechnologies.com - We provide data mining, eBay templates, web scraping, data extraction, web automation, Amazon automation, eBay automation services to our clients around the globe.
Launchpad Online: Automating YouTube stats with Google Apps Script
 
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Have you ever been asked by your boss to do something simple but long and tedious, such as counting up the view counts for your corporate videos and your competitors'? What about outside of work where you and your gamer friends are competing to see whose replay clips get the most views? This is a boring task that's easily processed from a Google Sheets spreadsheet with the help of Google Apps Script and the YouTube Data API. In this Launchpad Online episode, Google engineer Wesley Chun (http://google.com/+WesleyChun) and special guests propose a scenario that may not be so different from real life including a line-by-line code walkthough that can get you started building a solution in JavaScript that will make your boss' (and you) happy! LINKS * New to Google Apps Script video (http://www.goo.gl/1sXeuD) * Spreadsheet with Apps Script code (http://www.goo.gl/SVxoCt) * Apps Script Execution API documentation (http://www.goo.gl/ryD6Q3) - Subscribe to the brand new Firebase Channel: https://goo.gl/9giPHG
Views: 9719 Google Developers
Best Data Mining, Web Scraping and ebay Template Services
 
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http://www.datatudetechnologies.com/ - We provide data mining, eBay templates, web scraping, data extraction, web automation, Amazon automation, eBay automation services to our clients around the globe.
Best Data Mining, Web Scraping and ebay Template Services
 
00:35
www.datatudetechnologies.com - We provide data mining, eBay templates, web scraping, data extraction, web automation, Amazon automation, eBay automation services to our clients around the globe.
Views: 20 Iyna Hynes
Text Analytics With R | How to Connect Facebook with R | Analyzing Facebook in R
 
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In this text analytics with R tutorial, I have talked about how you can connect Facebook with R and then analyze the data related to your facebook account in R or analyze facebook page data in R. Facebook has millions of pages and getting emotions and text from these pages in R can help you understand the mood of people as a marketer. Text analytics with R,how to connect facebook with R,analyzing facebook in R,analyzing facebook with R,facebook text analytics in R,R facebook,facebook data in R,how to connect R with Facebook pages,facebook pages in R,facebook analytics in R,creating facebook dataset in R,process to connect facebook with R,facebook text mining in R,R connection with facebook,r tutorial for facebook connection,r tutorial for beginners,learn R online,R beginner tutorials,Rprg
Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources
 
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Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources Saurav Ghosh (Virginia Tech) Prithwish Chakraborty (Virginia Tech) Bryan Lewis (Virginia Tech) Maia Majumder (Massachusetts Institute of Technology) Emily Cohn (Boston Children's Hospital) John Brownstein (Harvard Medical School) Madhav Marathe (Virginia Tech) Naren Ramakrishnan (Virginia Tech) Real-time monitoring and responses to emerging public health threats rely on the availability of timely surveillance data. During the early stages of an epidemic, the ready availability of line lists with detailed tabular information about laboratory-confirmed cases can assist epidemiologists in making reliable inferences and forecasts. Such inferences are crucial to understand the epidemiology of a specific disease early enough to stop or control the outbreak. However, construction of such line lists requires considerable human supervision and therefore, difficult to generate in real-time. In this paper, we motivate Guided Deep List, the first tool for building automated line lists (in near real-time) from open source reports of emerging disease outbreaks. Specifically, we focus on deriving epidemiological characteristics of an emerging disease and the affected population from reports of illness. Guided Deep List uses distributed vector representations (ala word2vec) to discover a set of indicators for each line list feature. This discovery of indicators is followed by the use of dependency parsing based techniques for final extraction in tabular form. We evaluate the performance of Guided Deep List against a human annotated line list provided by HealthMap corresponding to MERS outbreaks in Saudi Arabia. We demonstrate that Guided Deep List extracts line list features with increased accuracy compared to a baseline method. We further show how these automatically extracted line list features can be used for making epidemiological inferences, such as inferring demographics and symptoms-to-hospitalization period of affected individuals. More on http://www.kdd.org/kdd2017/
Views: 96 KDD2017 video
Webinar: Automated Mining Block Generation
 
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Preparing mining blocks for scheduling no longer needs to be a manual, time-intensive task. The Maptek approach is simple and repeatable while maintaining flexibility for running calculations 'on the fly'. The integrated, 3D visualisation environment provides an intuitive interface that allows users to focus on validated results.
Views: 334 MaptekVideo
Airflow: Automating ETLs for a Data Warehouse, Natarajan Chakrapani, SF Python July 2018
 
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Natarajan Chakrapani, a software engineer at Optimizely, describes using Airflow to automate ETL pipelines for a data warehouse. Slides are available here: https://docs.google.com/presentation/d/1Vrm9CSVXgyQeu8Kyzm487Yk96_7wvZMd6lMmzALHrtU/edit#slide=id.p Like the talk? Please give our speaker a thumbs up! Join us live at other events on https://sfpython.org and https://pybay.com This video is through the generosity of our sponsor PlanGrid PlanGrid is creating software for the 10 trillion dollar construction industry. Our mission is to be the record set for every job site in the world. Construction is stuck in the past - we are bringing it into the future through field first mobile applications backed by advanced machine learning techniques. PlanGrid has adopted Python as it’s language of choice for rapidly building advanced file processing pipelines and cloud services optimized for mobile offline use. With Python as the backbone of our product, we’re a proud sponsor of the SF Python Meetup. https://plangrid.com
Views: 259 SF Python
Automated Software Defect Prediction Using Machine Learning
 
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Software code is composed of several components (e.g., several Java classes). Testing all these components can be a very expensive task. If we know which components are likely to be defective, we can concentrate testing on these components, increasing the chances of finding software defects while reducing testing effort. The task of software defect prediction is concerned with predicting which software components are likely to be defective, helping to increase testing cost-effectiveness. In this talk, I will show how software defect prediction can be performed by using automated machine learning approaches. I will also go through some important issues to be considered when using such automated approaches.
Views: 5425 Mike Bartley
Databite No. 106: Virginia Eubanks
 
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Virginia Eubanks speaks about her most recent book Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. Eubanks systematically shows the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhuman choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. Virginia Eubanks is an Associate Professor of Political Science at the University at Albany, SUNY. In addition to her latest book, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor, she is the author of Digital Dead End: Fighting for Social Justice in the Information Age and co-editor, with Alethia Jones, of Ain’t Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. For two decades, Eubanks has worked in community technology and economic justice movements. Today, she is a founding member of the Our Data Bodies Project and a Fellow at New America. Joining her to discuss data-based discrimination are powerhouses Alondra Nelson and Julia Angwin. Alondra Nelson is president of the Social Science Research Council and professor of sociology at Columbia University. A scholar of science, technology, and social inequality, she is the author most recently of The Social Life of DNA: Race, Reparations, and Reconciliation after the Genome. Her publications also include Body and Soul: The Black Panther Party and the Fight against Medical Discrimination; Genetics and the Unsettled Past: The Collision of DNA, Race, and History; and Technicolor: Race, Technology, and Everyday Life. Julia Angwin is an award-winning investigative journalist at the independent news organization ProPublica. From 2000 to 2013, she was a reporter at The Wall Street Journal, where she led a privacy investigative team that was a Finalist for a Pulitzer Prize in Explanatory Reporting in 2011 and won a Gerald Loeb Award in 2010. Her book, Dragnet Nation: A Quest for Privacy, Security and Freedom in a World of Relentless Surveillance, was published by Times Books in 2014. In 2003, she was on a team of reporters at The Wall Street Journal that was awarded the Pulitzer Prize in Explanatory Reporting for coverage of corporate corruption. She is also the author of “Stealing MySpace: The Battle to Control the Most Popular Website in America” (Random House, March 2009).
Text Analytics with R - Automating WordCloud in Shiny - Shiny web application tutorial
 
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In this text analytics with R tutorial, I've talked about how you can automate wordcloud in shiny so that you can focus more on analytics and less on code. You just need to supply the text file to shiny web application for wordcloud creation and shiny app will do all the heavy lifting of doing the background process and give you wordcloud for your text analytics. Shiny web application,r shiny,creating word cloud in r,automating wordcloud creation in R,text analytics in shiny,shiny text analytics,how to automate wordclouds in shiny,automating analytics,shiny tutorial,wordcloud shiny tutorial,automate wordclouds with shiny,using shiny to automate wordclouds,shiny for text analytics,shiny web application for text analytics,analyzing textual data with shiny,automating text analytics wordcloud in shiny,R Programming tutorial
Process Mining for SAP. What it is. How to do it.
 
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Worksoft provides the world’s leading automation platform for enterprise applications. Our fourth-generation platform provides automated business process discovery, documentation, compliance, testing, risk analysis, and RPA to support critical applications, including SAP, Oracle, Salesforce, Workday, SuccessFactors, ServiceNow, and more. For more information, contact Worksoft at [email protected] or visit www.worksoft.com.
Views: 290 worksoftinc
Web developer and web automation expert
 
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I'm a professional web developer and I'm specialized on web automations of any kind (crawlers, spiders, data mining, form posts) and I can automate anything that a user can or CAN'T do on web. Contact: [email protected] skype: marbalmedia
Views: 2291 Cristian Bal
Web Scraping, Screen Scraping, Web Data Mining, Data Extractor
 
06:28
Input FORMAT SUPPORT [website, webpage, Text, pdf, CSV, database] Output FORMAT SUPPORT [ excel, csv, tsv, pdf, xml, html, sql, MySql ] » Hotel website [ hotel name, address, images, reviews, latitude-longitude, price ] Scraping » Hotel price scraping for marketing intelligence [againast to your competitor] » Real Estate Data Extraction » Extract Store Details » University's Web Data Scraping » Extract Product Description » Web Information Extractor » Craigslist Email Extractor » Metadata Extraction » Website Email Extraction » Scraping Business Directory » Yellow Pages Scraping » PriceGrabber Data Extraction » Scraping Property Information » Amazon Product Extraction » Download Product Images » Automate osCommerce Product Upload » Scraping Business Contact » Craigslist Posting Service » Imdb Data Extraction » Meta Data Extraction » Scraping From Dynamic Pages » Extract Lyrics Data » Email Scraping & Extraction » Scraping Customer List » Scraping Data From WebSite ----------------------------------- Expertise In -------------------------- » Hotel Website Scraping [expedia.com, hotels.com, booking.com, orbitz.com, airasia.com, easybook.com, laterooms.com, travelocity.com, thomascook.com, activehotels.com, priceline.com, lastminute.com, yatra.com, makemytrip.com etc.] » Ads Classifieds Scraping [gumtree.com, olx.com, craigslist.com etc] » Real Estate Scraping [99acres.com, www.zillow.com, www.trulia.com, www.realtor.com, www.agentimage.com, www.realtysoft.com, www.realestate.com.au etc.] » Product catalog Scraping [amazon.com , ebay.com, yellowpage, whitepage etc.] Contact if any service require [ [email protected] ]
Views: 61776 vickyrathee2005
Jen Underwood on Data Visualization and Automating Data Science
 
44:17
Listen to the full episode here: http://datadriven.tv/jen-underwood-data-visualization-automating-data-science/ In this first episode, Frank and Andy chat with Jen Underwood, who's website is incredibly awesome. Links: Jen Underwood's blog About Jen Underwood Impact Analytix Sponsored by Enterprise Data & Analytics Cool Conversation Blurbs: Unicorns Among Us (1:42) - Note: Data Driven is an Audible Affiliate. You can pick up a free audio book and start a free 30-day trial at Audible.com. Jen discusses where she thinks data science is going. (9:15) The relationship between Data Science, Artificial Intelligence, Machine Learning (18:30) The Power of One (28:05) On blog post backlash (35:00) About Jen Underwood Jen Underwood, founder of Impact Analytix, LLC, is a recognized analytics industry expert. She has a unique blend of product management, design and over 20 years of “hands-on” development of data warehouses, reporting, visualization and advanced analytics solutions. In addition to keeping a constant pulse on industry trends, she enjoys digging into oceans of data. Jen is honored to be an IBM Analytics Insider, SAS contributor, former Tableau Zen Master, and active analytics community member. In the past, Jen has held worldwide product management roles at Microsoft and served as a technical lead for system implementation firms. She has launched new analytics products and turned around failed projects. Today she provides industry thought leadership, advisory, strategy, and market research. She also writes for InformationWeek, O’Reilly Media and other tech industry publications. Jen has a Bachelor of Business Administration – Marketing, Cum Laude from the University of Wisconsin, Milwaukee and a post-graduate certificate in Computer Science – Data Mining from the University of California, San Diego.
Views: 8 DataDriven
Introduction to Automating Complex Data Analysis
 
18:40
An introduction to our work on Automating Complex Data Analysis at Mathematical Software. E-Mail: [email protected] Web: http://www.mathematical-software.com/
Views: 62 John McGowan
Tellius Intelligent Data Discovery
 
03:42
Intelligent data discovery has amazing potential to alter today’s manual approaches to data visualization. Automating analytics with next-generation search and data discovery provides rapid insights powered by advanced analytics and artificial intelligence. Over the past few years, several vendors introduced smart data discovery concepts. Mainstream offerings are also slowly adding them. Today we are seeing an exciting new generation of savvy analytics vendors entering the market. One of these up and coming players is Tellius.
Views: 1063 Jen Underwood
ASI: Mine Site Automation
 
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For more than 14 years, ASI has been a world leader in OEM-independent automated vehicle solutions. From our northern Utah headquarters, ASI serves clients around the world in the mining, agriculture, automotive, military, and manufacturing industries with remote control, teleoperated, and fully automated, coordinated multi-vehicle solutions. We have years of experience automating mining equipment such as dozers, ADTs, rigid haul trucks, and excavators.
Intro to Web Scraping with Python and Beautiful Soup
 
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Web scraping is a very powerful tool to learn for any data professional. With web scraping the entire internet becomes your database. In this tutorial we show you how to parse a web page into a data file (csv) using a Python package called BeautifulSoup. In this example, we web scrape graphics cards from NewEgg.com. Sublime: https://www.sublimetext.com/3 Anaconda: https://www.continuum.io/downloads#wi... -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3500+ employees from over 700 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f6wzS0 See what our past attendees are saying here: https://hubs.ly/H0f6wzY0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... Vimeo: https://vimeo.com/datasciencedojo
Views: 384408 Data Science Dojo
José Manuel Ortega - Python tools for webscraping
 
44:31
PyData Madrid 2016 Most of the talks and workshop tutorials can be found here: https://github.com/PyDataMadrid2016/Conference-Info If we want to extract the contents of a website automating information extraction, often we find that the website does not offer any API to get the data you need and It is necessary use scraping techniques to recover data from a Web automatically. Some of the most powerful tools for extracting the data in web pages can be found in the python ecosystem. Introduction to webscraping WebScraping is the process of collecting or extracting data from web pages automatically. Nowdays is a very active field and developing shared goals with the semantic web field, natural language processing,artificial intelligence and human computer interaction. Python tools for webscraping Some of the most powerful tools to extract data can be found in the python ecosystem, among which we highlight Beautiful soup, Webscraping, PyQuery and Scrapy. Comparison between webscraping tools A comparison of the mentioned tools will be made, showing advantages and disadvantages of each one,highlighting the elements of each one to perform data extraction as regular expressions,css selectors and xpath expressions. Project example with scrapy Scrapy is a framework written in python for extraction automated data that can be used for a wide range of applications such as data mining processing. When using Scrapy we have to create a project, and each project consists of: 1.Items: We define the elements to be extracted. 2.Spiders: The heart of the project, here we define the extract data procedure. 3.Pipelines: Are the proceeds to analyze elements: data validation, cleansing html code Outline Introduction to webscraping(5 min) I will mention the main scraping techniques 1.1.WebScraping 1.2.Screen scraping 1.3.Report mining 1.4.Spiders Python tools for webscraping(10 min) For each library I will make and introduction with a basic example. In some examples I will use requests library for sending HTTP requests 2.1. BeautifulSoup 2.2. Webscraping 2.2. PyQuery Comparing scraping tools(5 min) 3.1.Introduction to techniques for obtain data from web pages like regular expressions,css selectors, xpath expressions 3.2.Comparative table comparing main features of each tool Project example with scrapy(10 min) 4.1.Project structure with scrapy 4.2.Components(Scheduler,Spider,Pipeline,Middlewares) 4.3.Generating reports in json,csv and xml formats
Views: 1426 PyData
203 Automating Unstructured Data Classification Malek Ben Salem
 
29:23
These are the videos from BSides NOVA 2018: http://www.irongeek.com/i.php?page=videos/bsidesnova2018/mainlist
Views: 108 Adrian Crenshaw
Data Entry Automation - Aitomation
 
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Data entry Automation is the process in which data entry work is automated with the help of bots. The bot performs the same actions as the individual previously doing so As a general,if you see.Data enry automation is all what we need today in all workplaces. In offices,there is a lot of data that is entered in systems daily. A data entry worker has to go through all files to access data which can be very tiring Time consumption is a big problem that is attached with data enrty. Which can of course lead workers to do errors. Automation dealt with this issue by automating such tasks which saved time. And In so doing,they came across these findings. Almost all employees spend 1 -3 hours daily for some redundant and repetitive work such as looking up data and copy pasting it. There was no proper way of handling errors. All of this was time consuming, frustrating for employees and with so many errors it was very inefficient. Whereas aitomation do it with simple clickable executable file to automate all of their tasks. There are many benefits of data entry automation like there will be no human errors There will be no excessive time consumption in data entry And since data entry is automated so you will no longer need data entry workers so this will be cost saving as well. Main goal of data entry automation is to streamline the process in a way that all human resource is used to optimize the process rather than slow it. Make sure there are checks at various steps to make sure there are no errors. To automate all of the tasks at hand from manual to data entry automation. For further info, please contact on any of the following : Contact at : [email protected] Website : http://aitomation.com/ Facebook : https://www.facebook.com/Aitomation/ Twitter : https://twitter.com/Aitomation1 LinkedIn : https://www.linkedin.com/company/aitomation Youtube : https://www.youtube.com/c/AitomationAI Instagram : https://www.instagram.com/aitomationai/ Tumblr : https://www.tumblr.com/blog/aitomation Google+ : https://plus.google.com/+AitomationLtd Pinterest : https://www.pinterest.com/aitomation/ Scoop it : http://www.scoop.it/u/aitomation Delicious : http://del.icio.us/aitomation Diigo : https://www.diigo.com/profile/aitomation SmugMug : https://aitomation.smugmug.com/ Vimeo : https://vimeo.com/aitomation Dailymotion: http://www.dailymotion.com/aitomation
Views: 124 Aitomation
Chemul: Automating Excerption in Chemical Data Curation
 
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Chemul, EPAM’s innovative solution for chemical data curation, consolidates all recognized reference books into one knowledge base and relies on crowdsourcing to control the content. Watch the video to learn more. ----- Check Us Out on Social Linkedin: https://www.linkedin.com/company/epam-systems Facebook: https://www.facebook.com/EPAM.Global/ Instagram: https://www.instagram.com/EPAMSystems/ Twitter: https://twitter.com/EPAMSystems/
Views: 545 EPAM Systems Global