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

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

General

• How we prepare future big data specialists
• Data Science template visualization is a vivid and interesting infographics.
• RStudio New Features (v0.99 Preview): Code Completion
• IPython: version 3.0 released
• Pulsar: eBay real-time data analysis framework
• Deep learning without the high costs - a small article from the portal HighScalability.com, which 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 Training: Spark MLlib
• Unusual Playboy models, or about detecting outliers in data using Scikit-learn
• AI from Google independently mastered 49 old Atari games
• Mistakes to avoid when using machine learning
• User research through Twitter data analysis and machine learning
• Machine learning errors - the author of this publication describes several common mistakes that those who use machine learning algorithms encounter in solving their problems.
• Google’s R Code Design Standards (Google’s R Style Guide)
• Does class balancing help improve classifier performance?
• 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
• Visualizing Clusters with R
• Comparison of learning algorithms with a teacher (Supervised learning)
• A series of lessons on machine learning and natural language processing. Lesson 4: Naive Bayes Classifier

Machine learning competitions

• Diary of the participants of the machine learning "Avazu Kaggle Challenge"
• Machine Learning Competition: Diabetic Retinopathy Detection

Online courses, educational materials and literature

• The 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

Video, podcasts

• Interview with Andrew Ng at the San Francisco Deep Learning Summit Conference
• Scaling machine learning with R and the H2O library
• Talking Machines: Episode 5: Interviews with Geoffrey Hinton, Yoshua Bengio and Yann LeCun: The Insider Learning History is the fifth episode of the “Talking Machines” podcast series, in this case, a session of communication 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
• Streaming Big Data: Storm, Spark and Samza
• Apache Spark big data processing
• Using MongoDb with Hadoop and Spark: Part 1 - Basics and Tuning
• Beginning of a new era: Release Apache HBase version 1.0
• Now you can download the beta version of Hive-on-Spark

Reviews

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

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