Edu-Video |”Building a Production Machine Learning Infrastructure” – Josh Wills /Dir. Data Scientist

(Reposted due to popular demand) Another great video from Josh Wills. Josh is Sr. Director of Data Science at Cloudera and has a gift for making fairly complicated technology explanations very digestible to the novice and intermediary techie.

What I most love about this video is how Josh explains -very clearly – the issue of translating analytics Machine Learning on a large set of data records (many individuals) and making it work well in a “real life” production environment on a single individual (think eCommerce). Watch Video

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Edu-VIDEO | Great Machine Learning Course from CalTech!- Lectures 1 thru 18 (free)

Great (free) Machine Learning course for beginners by Caltech University. Introduction to; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lectures 1 of 18 of Caltech’s Machine Learning Course – CS 156 by Professor Yaser Abu-Mostafa. Watch Video

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VIDEO | Dr. Andy Feng, VP Architecture at Yahoo! | “Large-Scale Machine Learning” | 2016 CSL Student Conference

The University of Illinois’ Coordinated Science Laboratory had it student run conference last month. This video is Dr. Andy Feng – VP Architecture at Yahoo! He leads the architecture and design of big data and machine learning initiatives. “In this talk, we illustrate Yahoo use cases and datasets, and explain the evolution of big-data technology stack.” Watch Video

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LIST | 500+ Data Science Degrees and Certificates from Universities (via Data Science Central)

“This list of 500+ was started in 2012, updated in 2014 and also very recently according to the author. It was compiled by 101.datascience.community, and broken down by degree (master / bachelor / certificate / doctorate) and location (online / on-site.)” – Source Data Science Central Read More

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Podcast | Understanding Predictive Analytics (O’Reilly)

In this episode of the O’Reilly Data Show, O’Reilly’s online managing editor Jenn Webb speaks with Natalino Busa on the topic of predictive analytics, the challenges of feature engineering, and a new class of techniques that is enabling features to emerge from patterns within the data.

They also discuss the relationship between predictive techniques and high-quality microservices, and how machine learning is being used to improve financial services. Listen to Podcast

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2016 Data Science Salary Survey and More | (Free eBook)

IN THIS FOURTH EDITION of the O’Reilly Data Science Salary Survey. They analyzed input from 983 respondents working in the data space, across a variety of industries— representing 45 countries and 45 US states.

Through the results of their 64-question survey, They’ve explored which tools data scientists, analysts, and engineers use, which tasks they engage in, and of course—how much they make. READ MORE

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Video | Strata + Hadoop World NYC 2016 | “The Evolution of Massive Scale Data Processing”

In this video, Tyler Akida presents a whirlwind tour of the evolution of massive-scale data processing at Google, from the original MapReduce paradigm to the high-level pipelines of Flume to the streaming approach of MillWheel to the portable, unified streaming/batch model of Google Cloud Dataflow and Apache Beam (incubating).

Tyler also highlights similarities and differences with related open source systems such as Flink, Spark, Storm, and Gearpump, calling out ways in which they’re converging on and diverging from the Beam model and what that means when running Beam pipelines on their respective runners. Watch Video

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