Overview of the most interesting materials on data analysis and machine learning No. 7 (July 28 - August 4, 2014)

I present to you the next issue of a review of the most interesting materials on the topic of data analysis and machine learning. There are several articles in this review that will be of interest to beginners. There are some interesting video lectures on Data Science. In the current issue, as usual, there are many articles on machine learning and data analysis with examples of code in the programming language R and Python. The review may also be of interest to several book reviews on data analysis.

Data Analysis and Machine Learning Materials

Introduction to Gaussian processes
An interesting introductory article on Gaussian processes, with Python examples that are often used when using machine learning algorithms in nonparametric regression and classification.
HighlightHTML library for R
A short article about the useful HighlightHTML library for the R programming language and for working with the html markup of R Markdown documents.
Data Science Using Python (Part 1)
The first part of a series of articles on Data Science using the Python programming language. The first part contains a video from the Pycon 2014 conference, and also focuses on collecting data for analysis using Python.
Creating and publishing interactive graphs ggplot2
An interesting article about the possibility of creating and publishing interactive graphs created using the ggplot2 package for the programming language R, online using the service plot.ly. This article provides some practical examples of using this service.
Yelp Data Analysis Competition The
popular Yelp portal has announced the launch of a new data analysis competition based on the data that Yelp will provide. This competition will run until December 31, 2014.
Book Review “Data Classification: Algorithms and Applications”
A brief review of the new book on data classification “Data Classification: Algorithms and Applications”. The review is presented by the popular resource KDnuggets.
The book "Neural Networks and Deep Learning" An
interesting book on the popular direction of machine learning. The book is not finished yet, but about half of the chapters of this very interesting book are already written and available to readers.
DataScienceCentral Weekly Digest
Regular weekly data analysis digest from DataScienceCentral.
Netflix's Xavier Amatriain video lectures on Netflix's Xavier Amatriain reference systems are another lecture series from Machine Learning Summer School (MLSS '14) in Pittsburgh. This series of video lectures is dedicated to recommendation systems.
Application of machine learning for trading (part 3)
Continuation of the topic of using machine learning for trading. This time, we are considering building a trading strategy based on a decision tree.
Kaggle Competition Solution List
An excellent list of solutions for some Kaggle Machine Learning competitions.
Using Cassandra in real-time systems An
interesting article on the topic of Data Engineering on how you can use the popular NoSQL-based Apache Cassandra solution for working with real-time systems.
Machine learning and text analysis
A short article on the use of machine learning in text analysis.
Recommendations everywhere
A small and fairly simple article from the Microsoft Technet Machine Learning Blog about how recommender systems work.
Want to learn SQL? There is an excellent starting course for beginners.
A popular blog on data analysis Data Science 101 has published a news that will be interesting for those who want to learn SQL, which obviously does not lose its significance and relevance during the growing popularity of various NoSQL solutions.
Introduction to Python Data Analysis
An excellent article on a brief introduction to data analysis using the Python programming language.
Data Science
Resource List An interesting Data Science resource list published on the DataScienceCentral portal.
Digest of the best resources from DataScienceCentral (July 28)
A good list of fresh interesting articles and resources from DataScienceCentral.
An example of using machine learning at Microsoft
A small example of using machine learning, namely Boosted Decision Trees (BDTs), at Microsoft Bing.
100 million images from Flickr from Yahoo Labs
Yahoo Labs said they published a large dataset of 100 million images and video clips under the Creative Commons license for various research.
Overview of Probabilistic Approaches to Recommendations
A brief overview of the new Probabilistic Approaches to Recommendations book.
What is machine learning?
A short article from John Platt, who has been with Microsoft for 17 years and has been actively using machine learning in his daily work. In this article, he talks about how machine learning is used to solve various problems in Microsoft projects.
Nonlinear regression with decision trees
Another article by Mahine Learning Mastery. This time we will talk about nonlinear regression with decision trees with code examples in the Python programming language.
The list of innovations in SAS / IML 12.3 The
list of innovations in SAS / IML 12.3.
20 years of machine learning at Microsoft
A short article about the fact that machine learning technologies have been used at Microsoft for quite some time and rich experience has been accumulated in this direction. Of course, the author mentions Microsoft Azure Machine Learning, a new cloud service from Microsoft for use in solving problems that require the use of machine learning techniques.
Real-time Queries for Cassandra with Spark and Shark
Even Chan, a developer at Ooyla in Silicon Valley, talks about the experience of using Spark and Shark frameworks on top of Cassandra to execute real-time queries.