Overview of the most interesting materials on data analysis and machine learning No. 32 (January 19 - 25, 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.
- Visualizing multidimensional data with Andrews charts
- Microsoft buys Revolution Analytics
- Best SlideShare Big Data Presentations - An updated version of the ranking of SlideShare's most popular Big Data presentations with some analytics from KDnuggets.com.
- Data Scientist: 5 Essential Skills
- 15 great data visualizations
- Researchers reveal machine learning network for distributed device groups
- Computers learn how to treat cancer and diabetes by playing atari and poker
- The history of the development of computer vision algorithms over the past 20 years
- Construction of a recommender system (part 1)
- A Few Words About Artificial Neural Networks and Deep Learning
- Building scalable machine learning algorithms
Theory and algorithms of machine learning, code examples
- Introduction to scikit-learn - this post provides an overview of the scikit-learn machine learning library.
- Data tidying: Preparing data sets for analysis using case studies
- Visualizing Deep Learning is a great article to help you better understand how Deep Learning works.
- Clustering by the k-means method: you have to pay for everything - a small curious article in which the author discusses the intricacies of the k-means clustering algorithm (k-means).
- A bit about convolutional neural networks
- Deep immersion in recurrent neural networks
- Kernel PCA Algorithm Overview
- Machine learning for face recognition - a good example of the use of machine learning algorithms for face recognition using scikit-learn library for Python programming language.
- Text Analysis for Beginners: Document Classification
- Convolutional neural network training game Go
- Model Performance (Part 2) - in this article, the author of the blog Analytics Vydhya will continue the topic of evaluating the performance of a predictive model.
- An introduction to caretEnsemble is a useful article on the caretEnsemble library that allows you to apply algorithmic compositions (Ensemble Methods) to models from the popular caret machine learning library for the programming language R.
- About decision trees in plain language is a good short description of decision trees from the Vidhya Analytics blog.
- Data Analysis in Python - Useful code examples for analyzing data using the Python programming language.
- Jetpack: Machine Learning Tools at Docker
- Major developer mistakes when using Python to analyze big data
- An example of using Random Forest and boosting with MLlib
- The Pandas Toolkit is a short list of useful code examples for the Pandas library for the Python programming language.
Machine Learning Competitions
- Getting Started at Kaggle: A Guide for Beginners in Data Science
- New Machine Learning Competition “How much did it rain?” - a few days ago at Kaggle a new machine learning competition “How much did it rain?” Began
Online courses, training materials and literature
- Start of Stanford University's Mining Massive Datasets online course - On January 31, Coursera will begin the second session of Stanford University’s Mining Massive Datasets online course.
- Book Review: Advanced Analytics with Apache Spark
- Free e-book: H2O and R - a free book about the H2O machine learning platform and its use with the programming language R.
- Introduction to Random Forest by Dr. Nando de Freitas - in this post a lecture on the popular machine learning algorithm Random Forest from Dr. Nando de Freitas (Adjunct Professor at UBC Computer Science, Full-time Professor at Oxford).
- Interesting from the world of R (January 19-25, 2015)
- DataScienceCentral Weekly Digest (January 26)
- Digest of the best resources from DataScienceCentral (January 23)
- Best Content of the Week from KDnuggets.com (January 11-17)
- Data Science News from MyDataMine.com (January 22)
- Best Resources of the Week from Data Elixir (No.19)
- The weekly collection of the best materials from R1Soft (January 23)
- The most interesting materials on High Scalability (January 23)
Previous issue: Overview of the most interesting materials on data analysis and machine learning No. 31 (January 12 - 18, 2015)