Strata Conference Santa Clara 2014: Complete Video Compilation

Table of contents

1. Tutorials
   1. Introduction to Machine Learning with IPython and scikit-learn - Olivier Grisel - Part 1
   2. Introduction to Machine Learning with IPython and scikit-learn - Olivier Grisel - Part 2
   3. Introduction to Machine Learning with IPython and scikit-learn - Olivier Grisel - Part 3
   4. Introduction to Machine Learning with IPython and scikit-learn - Olivier Grisel - Part 4
   5. IPython In Depth - Brian Granger and Fernando Prez - Part 1
   6. IPython In Depth - Brian Granger and Fernando Prez - Part 2
   7. IPython In Depth - Brian Granger and Fernando Prez - Part 3
   8. Building a Data Platform - John Akred, Richard Williamson, and Stephen O'Sullivan - Part 1
   9. Building a Data Platform - John Akred, Richard Williamson, and Stephen O'Sullivan - Part 2
   10. Building a Data Platform - John Akred, Richard Williamson, and Stephen O'Sullivan - Part 3
   11. Building a Data Platform - John Akred, Richard Williamson, and Stephen O'Sullivan - Part 4
   12. Design Thinking for Dummies (Data Scientists) - Michael Stringer, Dean Malmgren, and Laurie Skelly - Part 1
   13. Design Thinking for Dummies (Data Scientists) - Michael Stringer, Dean Malmgren, and Laurie Skelly - Part 2
   14. Design Thinking for Dummies (Data Scientists) - Michael Stringer, Dean Malmgren, and Laurie Skelly - Part 3
   15. Dissecting Data Science Algorithms using Spreadsheets - John Foreman - Part 1
   16. Dissecting Data Science Algorithms using Spreadsheets - John Foreman - Part 2
   17. Dissecting Data Science Algorithms using Spreadsheets - John Foreman - Part 3
   18. Dissecting Data Science Algorithms using Spreadsheets - John Foreman - Part 4
   19. Introduction to Hadoop 2.0 - Rich Raposa - Part 1
   20. Introduction to Hadoop 2.0 - Rich Raposa - Part 2
   21. Introduction to Hadoop 2.0 - Rich Raposa - Part 3
   22. Introduction to Hadoop 2.0 - Rich Raposa - Part 4
   23. Large-scale Machine Learning Cookbook using GraphLab - Carlos Guestrin - Part 1
   24. Large-scale Machine Learning Cookbook using GraphLab - Carlos Guestrin - Part 2
   25. Large-scale Machine Learning Cookbook using GraphLab - Carlos Guestrin - Part 3
   26. Large-scale Machine Learning Cookbook using GraphLab - Carlos Guestrin - Part 4
   27. From Scattered to Scatterplots: An Introduction to d3.js - Scott Murray - Part 1
   28. From Scattered to Scatterplots: An Introduction to d3.js - Scott Murray - Part 2
   29. From Scattered to Scatterplots: An Introduction to d3.js - Scott Murray - Part 3
   30. From Scattered to Scatterplots: An Introduction to d3.js - Scott Murray - Part 4
   31. Effective Data Science With Scalding - Vitaly Gordon - Part 1
   32. Effective Data Science With Scalding - Vitaly Gordon - Part 2
   33. Big Data Workflows on Mesos Clusters - Florian Leibert, Paco Nathan, and Benjamin Hindman - Part 1
   34. Big Data Workflows on Mesos Clusters - Florian Leibert, Paco Nathan, and Benjamin Hindman - Part 2
   35. Big Data Workflows on Mesos Clusters - Florian Leibert, Paco Nathan, and Benjamin Hindman - Part 3
   36. Big Data Workflows on Mesos Clusters - Florian Leibert, Paco Nathan, and Benjamin Hindman - Part 4
   37. Adviser: Learning How to get A Second Opinion on Your Analysis when it's Important to get it Right - Leland Wilkinson - Part 1
   38. Adviser: Learning How to get A Second Opinion on Your Analysis when it's Important to get it Right - Leland Wilkinson - Part 2
   39. Adviser: Learning How to get A Second Opinion on Your Analysis when it's Important to get it Right - Leland Wilkinson - Part 3
   40. Building Real-Time Apps with Apache HBase - Ronan Stokes - Part 1
   41. Building Real-Time Apps with Apache HBase - Ronan Stokes - Part 2
   42. Building Real-Time Apps with Apache HBase - Ronan Stokes - Part 3
   43. Building Real-Time Apps with Apache HBase - Ronan Stokes - Part 4
   44. Data Transformation: Skills of the Agile Data Wrangler - Joe Hellerstein, and Jeffrey Heer - Part 1
   45. Data Transformation: Skills of the Agile Data Wrangler - Joe Hellerstein, and Jeffrey Heer - Part 2
2. Hardcore Data Science
   1. Hardcore Data Science Opening Remarks - Ben Lorica
   2. Extreme Machine Learning - Alexander Gray
   3. What the #@)*$ is Big Data? A Holistic View of Data and Algorithms - Alice Zheng
   4. Overcoming the Barriers to Production-Ready Machine-Learning Workflows - Henrik Brink, and Joshua Bloom
   5. Anomaly Detection - Ted Dunning
   6. Neural Networks for Machine Perception - Ilya Sutskever
   7. The Predictive Business - Kira Radinsky
   8. Can We Make Big Data Management Easier? - Magda Balazinska
   9. Design Challenges for Real Predictive Platforms - Max Gasner
   10. Machine Learning Gremlins - Ben Hamner
   11. Algebra for Scalable Analytics - Oscar Boykin
3. Data-Driven Business Day
   1. Introduction to Data Driven Business Day - Alistair Croll
   2. Those Numbers Wont Measure Themselves - Farrah Bostic
   3. Social Data Intelligence: Integrating Social and Enterprise Data for Competitive Advantage - Susan Etlinger
   4. Open Data: Its Not Just for Governments - Jen van der Meer
   5. The Insight Economy - Krista Schnell
   6. 9 Levers for Converting Big Data and Analytics into Results - Christy Maver
   7. Deploying a Data Sciences Team -- The Promise and the Pitfalls - Diane Chang
   8. Sensing Best Practices - Ben Waber
   9. Leveraging Value from Open Data Through Collaboration -Peter Pirnejad
   10. Becoming a Learning Organization: From Data Teams to Corporate Influence - Pamela Peele
   11. Making Big Data Small - Baron Schwartz
   12. Big Data Meets Big Infrastructure: Going Underground in One Major European City - Narendra Mulani
   13. The Era of Data-Powered Government - Beth Blauer
   14. TripIt Uses Data to Organize Itineraries, No Matter Where You Book - Edith Harbaugh
4. Keynotes
   1. Crossing the Chasm: What's New, What's Not - Geoffrey Moore
   2. Evolution from Apache Hadoop to the Enterprise Data Hub - Amr Awadallah
   3. Collecting Massive Data via Crowdsourcing - John Schitka
   4. Empowering Personalized Learning with Big Data - Ramona Pierson
   5. Hadoop in 5 Minutes or Less - John Schroeder
   6. People are Data Too - Farrah Bostic
   7. Bringing Big Data to One Billion People - Quentin Clark
   8. Small Data in Sports: Little Differences that Mean Big Outcomes - David Epstein
   9. The Art of Good Practice - Rodney Mullen
   10. Big Data Moonshots and Ground Control - Joe Hellerstein and Tutti Taygerly
   11. Data Science and Smart Systems: Creating the Digital Brain - Kaushik Das
   12. How Companies are Using Spark, and Where the Edge in Big Data Will Be - Matei Zaharia
   13. In-Hadoop Analytics: Bringing analytics to big data - Anjul Bhambhri
   14. Record Linkage and Other Statistical Models for Quantifying Conflict Casualties in Syria - Megan Price
   15. Ben Fry Keynote
   16. Survivorship Bias and the Psychology of Luck - David McRaney
5. Sessions
   1. Apache Hadoop and the Emergence of the Enterprise Data Hub - Eli Collins
   2. Information Visualization for Large-Scale Data Workflows - Michael Conover
   3. Adaptive Adversaries: Building Systems to Fight Fraud and Cyber Intruders - Ari Gesher
   4. Fighting Global Cybercrime and BotNets using Big Data - Bryan Hurd and Herain Oberoi
   5. Navigating the Big Data Vendor Landscape - Edd Dumbill
   6. Best Practices for Hadoop In Production - Panel Discussion Facilitated by Forrester Analyst - Mike Gualtieri
   7. Thorn in the Side of Big Data: Too Few Artists - Chris Re
   8. 10,000: The Most Dangerous Number in Sports - David Epstein
   9. You're Halfway There: Moving from Insight to Action - Bob Filbin
   10. Building the Next Generation Data Architecture with Hadoop, Data Warehouse Data Discovery Platform - Bill Franks
   11. Minority Report Meets Big Data: Touch and Interactive Big Data is Here - Justin Langseth, and Eva Andreasson
   12. Machine Learning for Social Change - Fernand Pajot
   13. Harness Data in Real-Time with Infinite Storage - Yuvaraj Athur Raghuvir
   14. You Don't Need to Boil the Big Data Ocean with Hadoop - Ben Werther, and Sanjay Mathur
   15. Predictive Modeling in the Cloud with Scikit-learn and IPython - Olivier Grisel
   16. Mining Student Notes in Real Time to Provide Study Guides - Perry Samson
   17. Thinking with Data - Max Shron
   18. Building a Data-centered Data Center for Agile Development - Justin Makeig
   19. Evolving Data Governance for the Big Data Enterprise - Scott Lee and Rachel Haines
   20. Making Big Data Cost Effective in a Bare Metal Cloud - Harold Hannon
   21. How Evernote Does Conversion Using Hadoop Analytics - Damon Cool
   22. Crowdsourcing at Locu: How I Learned to Stop Worrying and Love the Crowd - Adam Marcus
   23. Building a Lightweight Discovery Interface for Chinese Patents - Eric Pugh
   24. Superconductor: Scaling Charts with Design and GPUs - Leo Meyerovich
   25. Break Down Data Silos with Apache Accumulo - Adam Fuchs
   26. Organizing Big Data with the Crowd - Lukas Biewald
   27. Scalable PostgreSQL as your data platform - Ben Redman
   28. Unlocking the Secrets of Gertrude Stein - Ian Timourian
   29. A Different Look at Data and Security - Learning to Live with Fear - Pablos Holman
   30. Stand Back, I'm Going To Try Science! - Rachel Poulsen and John Akred
   31. Collaborative Advanced Analytics For Big Data - Bruno Aziza
   32. Network Science Made Simple: SNA for Pie Chart Makers - Marc Smith
   33. How Twitter Monitors Millions of Time-series - Yann Ramin
   34. Harvard's Clean Energy Project: Big Data Maps To Renewable Energy - Kai Trepte
   35. Working With Time Series Data Using Apache Cassandra - Patrick McFadin
   36. Friending Graph Analytics: Large-Scale Graph Processing Made Easy - Ted Willke
   37. Transforming Search Engine Marketing at Ask.com - Mohit Sati
   38. Music Videos and Gastronomification for Big Data Analysis - Brian Abelson, and Thomas Levine
   39. Soylent Mean: Data Science is Made of People - Cameran Hetrick and Kimberly Stedman
   40. Big Data: Beyond Bare-Metal? - Mike Wendt
   41. Secrets of Apache Hive Queries and UDFs - Shrikanth Shankar
   42. Twitter and HP HAVEn: The Big Data Big Picture - Sanjay Goil
   43. Data Science How to Build and Deploy a Team of Data Scientists - Diane Chang, Steven Hillion, Nick Kolegraff, and Matthew Gee
   44. The Netflix Data Platform - A Recipe for High Business Impact - Kurt Brown
   45. Bedtime Stories: Learning from Sleep Data - Monica Rogati
   46. Tracking a Soccer Game with Big Data - Srinath Perera
   47. Data Transformation: A User-Centric Approach to Accessing and Analyzing Big Data - Joe Hellerstein
   48. Apache Hadoop 2.0: Migration from 1.0 to 2.0 - Vinod Kumar Vavilapalli
   49. Getting a Handle on Hadoop and its Potential to Catalyze a New Information Architecture Model - Milan Vaclavik
   50. The Sidekick Pattern: Using Small Data to Increase the Value of Big Data - Abe Gong
   51. Exascale Data Analytics @ Facebook - Sambavi Muthukrishnan
   52. Sending Millions of Surveys Around the World on Mobile Phones - Max Richman
   53. Business Data Lake: An Evolution in Data Infrastructure - Jeffrey Kelly, Steven Hirsch, Steve Jones, and Sabrina Dahlgren
   54. Expressing Yourself in R - Hadley Wickham
   55. Data Journalism - Organized Crime and Corruption Reporting - Drew Sullivan
   56. The Inflection Point - Hadoop and Big Data Analytics - Anjul Bhambhri
   57. Spreadsheets: The Dark Matter of Big Data - Felienne Hermans
   58. Scale-Invariant Intelligence - Vin Sharma
   59. Probabilistic Programming: What, Why, How, and When - Beau Cronin
   60. Beyond Hadoop MapReduce: Interactive Advertising Insights with Shark @ Yahoo! - Nandu Jayakumar and Tim Tully
   61. Machine Learning for Machine Data - David Andrzejewski - Part 1
   62. Machine Learning for Machine Data - David Andrzejewski - Part 2
   63. Lessons from the Trenches: edo Interactive Leverages Hadoop to Build Customer Loyalty - Rob Rosen, and Tim Garnto
   64. The IPython Notebook: Get Close to Your Data with Python and JavaScript - Brian Granger
   65. Government Data on Both Sides of the Bridge - Moderated by: Jesse Robbins - Panelists: Shannon Spanhake and Eddie Tejeda
   66. Enabling Business Transformation with Analytics over Real-time Streaming Data - Anand Venugopal, and Pranay Tonpay
   67. The Next Wave of SQL-on-Hadoop: Building a Virtual EDW on Native Hadoop Data - Marcel Kornacker
   68. How Comcast Turns Big Data into Real-Time Operational Insights - Patrick Shumate
   69. Chicago Bars, Prisoners Dilemma, and Practical Models in Search -Chris Harland
   70. Big Industrial Internet Data: Connecting and Optimizing at New Scales - Steven Gustafson and Parag Goradia - Part 1
   71. Big Industrial Internet Data: Connecting and Optimizing at New Scales - Steven Gustafson, and Parag Goradia - Part 2
   72. FAST and FURIOUS Big Data Analytics Meets Hadoop - Wayne Thompson, and Paul Kent
   73. The Urgent Need to Appify Big Data - Ryan Cunningham
   74. Unboxing Data Startups - Michael Abbott
   75. Apache Hive Stinger: Petabyte Scale SQL, IN Hadoop - Owen O'Malley, and Alan Gates
   76. Querying Petabytes of Data in Seconds - Reynold Xin, and Sameer Agarwal
   77. The Need for Speed Scale: A Database for Real-Time Analytics - Eric Frenkiel
   78. Graph All The Things! 11: Graph Database Use Cases That Aren't Social - Emil Eifrem
   79. Graph Analysis with One Trillion Edges on Apache Giraph - Avery Ching
   80. Big Data for Big Power: Smart Meters does not mean Smart Grids - Brett Sargent
   81. The Last Mile: Challenges and Opportunities in Data Tools - Wes McKinney
   82. Are We Data Scientists or Data Janitors? - Nenshad Bardoliwalla
   83. Session with Ben Fry
   84. Data for Good - Moderated by: Jake Porway - Panelists: Drew Conway, Rayid Ghani, and Elena Eneva
   85. NonStop HBase - Making HBase Continuously Available for Enterprise Deployment - Jagane Sundar
   86. Apache Mesos as an SDK for Building Distributed Frameworks - Paco Nathan
   87. Agile Analytics - Neal Ford
   88. Socializing Search. Professionally. - Sriram Sankar, and Daniel Tunkelang
   89. Big Data for Better Data Centers - Krishna Raj Raja and Balaji Parimi
   90. One Size Does Not Fit All: Analyzing Data at Scale with AWS - Rahul Pathak
   91. Making Choices: What Kind of Relationship are You Seeking with Your Database? - J.R. Arredondo
   92. StatusWolf: Creating Dashboards That Don't Suck Using Art and Engineering - Mark Troyer
   93. Real-Time Analytics with NewSQL: Why Hadoop is not enough - Raj Bains
   94. MLbase: Distributed Machine Learning Made Easy - Ameet Talwalkar and Evan Sparks
   95. Real-time Analytics with Open Source Technologies - Fangjin Yang, and Gian Merlino