Overview of the most interesting materials on data analysis and machine learning No. 30 (January 5 - 11, 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

•   Data Science Cheat Sheets - A good list of different Data Science cheat sheets.
•  Outlook Data Science is an interesting Q & A session from the Microsoft Technet SQL Server blog with two Microsoft Data Scientists.
•   How to choose a project for your Data Science portfolio
•    Don’t worry, Python does not replace R
•  The main trends in the labor market in the field of Big Data, which are worth paying attention to in 2015
•  24 useful resources on the topic of Data Science - a good list of resources that will help you to keep abreast of the latest developments in the field of Data Science.
•  9 skills that will be necessary in 2015 to work in the field of Big Data
•  9 tips to help make Data Mining more effective

Theory and algorithms of machine learning, code examples

•   Trivium of measurement theory
•   Analysis of data from smartphone sensors using R and BreakoutDetection library
•   New version of Caret library - A new version of the popular Caret library for machine learning for the programming language R appeared in CRAN. This short post describes the main innovations of this version.
•   Python libraries for data analysis
•   What is scikit-learn? Is a short description of the popular scikit-learn machine learning library for the Python programming language from the author of the blog Analytics Vidhya.
•   Wearable machine learning using scikit-learn and Python
•   Anomaly Detection in Time Series - An article on Twitter about an interesting new library for the open-source programming language R, AnomalyDetection, for detecting anomalies in time series.
•   Using the AnomalyDetection library on Wikipedia Page View Data is a continuation of the Twitter AnomalyDetection library.
•   How does linear regression work? - in a simple language about linear regression.
•    Clearly about neural networks - a short article with an illustrated description of the operation of neural networks.
•  Random separation of data into test and training sets: this may not be enough
•   Image processing and feature selection using Python
•   An example of visualizing a Kalman filter using R

Machine Learning Competitions

•   BudgetApps - The First All-Russian Open Financial Data Competition
•   Machine Learning Rule Metrics: ROC and AUC
•  Winner Report "Getting a Handel on Data Science" at Kaggle InClass
•  AI Angry Birds Competition

Online courses, training materials and literature

•   Beginning of the new Artificial Intelligence Planning online course - early next week, Coursera will begin the Artificial Intelligence Planning course presented by The University of Edinburgh.
•   Course “Image and video processing” at Coursera - On January 5, Coursera began a new session of the popular online course “Image and video processing: From Mars to Hollywood with a stop at the hospital” from Duke University.
•   The Computational Methods for Data Analysis course has begun - the next session of the fairly popular Computational Methods for Data Analysis course from the University of Washinton began a few days ago at Coursera.
•    Online Course "Data Analysis and Visualization Using R"
•   Book: “Introduction to Probability, Statistics, and Random Processes”
•   Book: “Data Driven: Creating a Data Culture”

Videos

•   Best Strata + Hadoop World Speeches - This post presents a list of the best speeches from Strata + Hadoop World conferences.

Data engineering

•   New new thing (The new new thing)
•   Big Data on your computer: How to install Hadoop 2.6.0
•  Spark SQL Data Sources API: Unified Data Access with Apache Spark
•   Free eBook: Field Guide To Hadoop
•  Apache Samza: Streaming Information from LinkedIn

Reviews

•   Interesting from the world of R (January 5-11, 2015)
•  DataScienceCentral Weekly Digest (January 12)
•  Best Content of the Week from KDnuggets.com (December 28 - January 3)
•  Digest of the best resources from DataScienceCentral January 6)
•  Data Science News from MyDataMine.com (January 8)
•  Big Data News from MyDataMine.com (January 9th)
•  The weekly collection of the best materials from R1Soft (January 9)
•  Best Resources of the Week from Data Elixir (No.17)
•  The most interesting materials from Freakonometrics №201
•  The most interesting materials from Freakonometrics No. 202
•  The most interesting materials on High Scalability (January 9)

Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 29 (December 29, 2014 - January 4, 2015)