Review of the most interesting materials on data analysis and machine learning №31 (January 12

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

5 trends in data analysis and processing in 2015
Examples of the work of the genetic algorithm - I met two very clear examples of the work of genetic algorithms with a sufficiently large number of adjustable parameters.
An excellent collection of various data sets - a collection of various data sets from Sebastian Raschka.
NASA will resort to using machine learning when studying stars
Developing Deep Learning in Google Search is a very interesting article called “Google Search Will Be Your Next Brain” from a series of articles on search engine development in Google. This article will focus on the emergence and development of Deep Learning techniques in the company, the purchase of DeepMind, the development of the Google Brain project and artificial intelligence technologies.
Interview with Demis Hassabis - a continuation of the previous article, an interview with Demis Hassabis - the founder of DeepMind, which Google bought for $ 400 million.
Open source tools from Facebook to better utilize Deep Learning techniques.
Baidu builds a deep learning supercomputer
How to conduct an interview for the position of Data Scientist
Talking Machines: Episode 2: Interview with Ilya Sutskever - the second episode of "Talking Machines", in this case, this interview with Ilya Sutskever - one of the members of the Google Research team.
8 Big Data trends in 2015 according to DataFloq
R does not lose its relevance - a little reflection on the popularity of the R programming language and that it does not lose its popularity, and even vice versa.
Python vs. R: What to learn first? - in continuation of the topic of discussion of programming languages for data analysis - a good comparison from the author of the blog Udacity of two popular languages that are used for data analysis at the present time and the obvious, I think, conclusion at the end.
5 failures of 2014 in the field of work with data
10 Big Data Experts to Know
12 best stories last year in the field of Big Data

Theory and algorithms of machine learning, code examples

Their Yandex News with preference and courtesans
Event Analytics
Introduction to machine learning using Python and Scikit-Learn
Art Feauture Engineering in Machine Learning
The method of main components in 3 simple steps is another excellent article from Sebastian Raschka. In this case, he will tell about the basics of the Principal Component Analysis method.
What is deep learning? - A good introductory article, explaining the machine learning method Deep Learning, which is rapidly gaining popularity.
Deep Learning Overview
Geometry of classifiers - this article develops the topic of a fairly popular study “Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?” With examples of code in the Python programming language.
Deep Learning Python Examples
Load Balancing with RStudio Server Pro
Using the microbenchmark library to compare the execution times of various expressions in R
Run R in parallel mode (easy way)
About decision trees in simple language
Model performance (Part 1) - Analytics blog author Vydhya will help you figure out how effective your predictive model is and tell you about possible ways to measure model performance.
Fundamental Data Science Methods: Classification, Regression, and Similarity Comparison
An example of visualization of the extended Kalman filter with R - continuation of the article “An example of visualization of the Kalman filter with R” from the previous review, in this case, an example of visualization of the extended Kalman filter (EKF, Extended Kalman filter) using the R programming language
Sample Code: R: Total Vectorization

Machine learning competitions

The machine learning competition of the “National Data Science Bowl” - not so long ago at the Kaggle began the new competition for machine learning of the “National Data Science Bowl”.
The results of the competition "Angry Birds AI Competiton"
Machine Learning Competition: ChaLearn Automatic Machine Learning Challenge (AutoML)

Online courses, educational materials and literature

Big Data for Business is a new paid course on the topic of Big Data in Russian with the possibility of learning both offline and online. Duration of training is 3 months. Classes 3 times a week for 3 hours. Certificate at the end of training.
The next session of “Machine Learning” by Andrew Ng - on January 19, the next session of the most currently popular online machine learning course starts.
The Statistical Learning course starts - on January 19, Stanford Online starts an interesting machine learning course called Statistical Learning.
The beginning of the course "Statistics and R for the Life Sciences" - January 19 begins an interesting course called "Statistics and R for the Life Sciences" from Harvard University at edX.
Free ebook: “Rabbit. Introduction to R is a good book on the basics of R, which is an accompaniment to the online course “Introduction to R”.

Data engineering

Reviews

Previous release: Review of the most interesting materials on data analysis and machine learning №30 (January 5 - 11, 2015)

Review of the most interesting materials on data analysis and machine learning №31 (January 12 - 18, 2015)

General

Theory and algorithms of machine learning, code examples

Machine learning competitions

Online courses, educational materials and literature

Data engineering

Reviews

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