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Oreilly - Strata Conference Santa Clara 2014 Part1 Training

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Oreilly - Strata Conference Santa Clara 2014 Part1 Training

Oreilly - Strata Conference Santa Clara 2014 Part1
English | Size: 6.72GB | Audio: aac, 44100 Hz, stereo | Video: h264, yuv420p, 1280x720, 25.00 fps(r)
By O'Reilly Media, Inc. | Publisher: O'Reilly Media | Released: March 2014
Genre: E-learning




The future belongs to those who understand data
Gain a clear perspective on the future of big data-and all the analytics, architectures, techniques, tools, and technologies you need to use data successfully.
With this complete video compilation, you'll get a front-row seat to the keynotes, workshops, and sessions at O'Reilly's Strata Conference Santa Clara 2014.

Explore the changes big data, data science, and pervasive computing have brought to technology and business with presentations from Matei Zaharia (Databricks), David McRaney (Raycom Media), Carlos Guestrin (GraphLab), Kira Radinsky (SalesPredict), scores of other experienced data practitioners from finance, media, government, and education.

these videos or stream them through our HD player, and capture the knowledge offered in Strata's 7 tracks: Data Science; Data in Action; The Connected World; Design; Ethics, Privacy, and Policy; Hadoop and Beyond; and Machine Data.

Learn the latest techniques in machine learning, prediction, and technology
Discover how to build effective data teams and create a data-driven organizational culture
See real-world case studies of large-scale, innovative big data applications-complete with behind-the-scenes insights
Explore the promises and perils of an always-on and increasingly quantified society, from the reach of government to the rights of the digital persona
Learn how to convey knowledge, from designing compelling interfaces to guiding users through a complex, immersive user experience
Dive into tools that make the big data revolution possible-Hadoop, Cassandra, Storm, Spark/Shark, and Drill-and extend your data science toolkit
Harness the flood of information from the Internet of Things and learn about the tools for collecting, storing, and analyzing it all

Part 1 Included
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
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