Overview of the most interesting materials on data analysis and machine learning No. 37 (February 23 - March 1, 2015)

I present to you the next issue of a review of the most interesting materials on the topic of data analysis and machine learning.

General

•   How we train future big data professionals
•  Visualization of Data Science templates is a visual and interesting infographic.
•   New features of RStudio (v0.99 Preview): Code Completion
•   IPython: version 3.0 released
•  Pulsar: eBay real-time data analysis framework
•  Deep learning without high costs - a small article from the HighScalability.com portal that tells you that you can start your experiments with Deep Learning now without any large financial investments.
•    Machine Learning Libraries - a large list of machine learning libraries, presented in the form of a periodic table and divided into several categories: Big Data, Lua / JS / Clojure, Computer Vision, NLP, C / C ++, R / Julia, Java, Scala, Python.

Theory and algorithms of machine learning, code examples

•    Big Data Learning: Spark MLlib
•    Unusual Playboy models, or about detecting outliers in data using Scikit-learn
•  Google AI mastered 49 old Atari games on its own
•   Mistakes to Avoid Using Machine Learning
•   User Learning Through Twitter Data Analysis and Machine Learning
•   Machine Learning Errors - the author of this publication describes several typical errors that those who use machine learning algorithms to solve their problems face.
•   Google R Code Design Standards (Google's R Style Guide)
•   Does balancing classes improve classifier results?
•  The K prediction algorithm in the k-means clustering algorithm is an interesting feature in the BigML library.
•  Deep Speech: Accurate Speech Recognition with Deep Learning and GPU
•   Visualization of clusters using R
•   Comparison of learning algorithms with a teacher (Supervised learning)
•   A series of lessons in machine learning and natural language processing. Lesson 4: Naive Bayes Classifier

Machine Learning Competitions

•  Avazu Kaggle Challenge Machine Learning Session Participants Diary
•  Machine Learning Contest: Diabetic Retinopathy Detection

Online courses, training materials and literature

•   Announcement of the new course: Introduction to Data Science - it is worth noting that the course is paid.
•    Book Review: Mastering Scientific Computing with R
•   Free eBook: Hadoop for Dummies
•   Free eBook: Software Defined Storage for Dummies

Videos, podcasts

•   Interview with Andrew Ng at the Deep Learning Summit in San Francisco
•   Machine Learning Scaling with R and the H2O Library
•  Talking Machines: Episode 5: Interviews with Geoffrey Hinton, Yoshua Bengio, and Yann LeCun: The Inside Machine Learning Story is the fifth episode of the Talking Machines podcast series, in this case a session with bison like Geoffrey Hinton (Google, University of Toronto ), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook, NYU).

Data engineering

•   Apache Spark: what's under the hood?
•  Real-time log analysis with Apache Kafka, Cloudera Search and Hue
•  Big Data Streaming: Storm, Spark, and Samza
•  Big Data Processing in Apache Spark
•  Using MongoDb with Hadoop and Spark: Part 1 - Basics and Customization
•  Beginning of a New Era: Apache HBase Version 1.0 Release
•  Now you can download beta version of Hive-on-Spark

Reviews

•   Interesting from the world of R (February 23 - March 1, 2015)
•  Best Content of the Week from KDnuggets.com (February 15-21)
•  DataScienceCentral Weekly Digest (March 2)
•  Data Science News from MyDataMine.com (February 27)
•  Big Data News from MyDataMine.com (February 24)
•  Best Resources of the Week from Data Elixir (No.24)
•  The weekly collection of the best materials from R1Soft (February 27)
•  The most interesting materials on High Scalability (February 27)

Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 36 (February 16 - 22, 2015)