Overview of the most interesting materials on data analysis and machine learning No. 34 (February 2 - 8, 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

•  Online Dating Machine Learning
•  Artificial intelligence can watch videos and describe what it sees - a curious post with a short video about the startup Clarify, which specializes in the field of artificial intelligence and develops a product that can describe what is happening in the proposed videos based on the use of Deep Learning algorithms.
•  Four great data visualizations
•  6 tips to help you become a great Data Science Specialist
•  One of the creators of Google Brain talks about why he is currently working on creating Chinese neural networks - an interesting interview with Andrew Ng.
•   Why do many data analysts choose Python? - An interesting question asked on Quora, and some useful answers.
•    Data Science: Should I study Python or R?
•   Why now is the time to learn the R programming language

Theory and algorithms of machine learning, code examples

•    Feature Engineering Example in Machine Learning
•    Automatic age rating system for facial images
•  How Shazam music recognition algorithm works
•   Practical Data Science with Python
•   A series of lessons in machine learning and natural language processing. Lesson 1: Working with Text
•   Understanding text from scratch is a post by Xiang Zhang and Yann LeCun on the use of convolutional neural networks for text analysis.
•   A few words about Shiny is a short post that will tell you about the popular Shiny visualization library for the R programming language and the possibilities of publishing your Shiny applications on the Shinyapps.io portal.
•   Quickcheck: randomized unit testing for R - a short post about an interesting unit testing library for the programming language R.
•   Pandas data analysis is a small example of using the Pandas library, written for the Python programming language, to analyze data.
•   Machine learning result

Online courses, training materials and literature

•   Book Review: High-Performance Data Mining and Big Data Analytics

Videos, podcasts

•  Partially Derivative: Episode 12: Partially Deflated is another episode of the popular podcast “Partially Derivative”.

Data engineering

•  Google again recorded the largest quarterly spending on data centers
•  Can Microsoft Cosmos compete with Hadoop
•  Using Apache Crunch to process data in Spotify is an interesting article; for those who use MapReduce, they are not yet ready to use Apache Spark, but want to get similar features.
•  Published Apache Hive 1.0.0

Reviews

•   Interesting from the world of R (February 2-8, 2015)
•   Interesting from the world of R (January 26 - February 1, 2015)
•  Best January Materials from KDnuggets.com
•  Best Content of the Week from KDnuggets.com (December 25 - 31)
•  Digest of the best resources from DataScienceCentral (February 5)
•  Data Science News from MyDataMine.com (February 6)
•  Big Data News from MyDataMine.com (February 3)
•  The weekly collection of the best materials from R1Soft (February 6)
•  Best Resources of the Week from Data Elixir (No.21)
•   This Month in the Hadoop Ecosystem (January 2015)
•  The most interesting materials on High Scalability (February 6)

Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 33 (January 26 - February 1, 2015)