Overview of the most interesting materials on data analysis and machine learning №12 (September 1 - 8, 2014)

I present to you the next issue of the review of the most interesting materials on the topic of data analysis and machine learning. This release has turned out quite voluminous, it has a lot of materials on Data Engineering. More and more materials appear from the KDD 2014 conference. As usual, there are articles about various machine learning competitions, including articles about the recent “ImageNet Large Scale Visual Recognition Challenge (ILSVRC)” competition. There are also quite a few examples of code in the R and Python programming languages. There is a mention of, I think, a very curious online course on “Introduction to Computational Finance and Financial Econometrics”.

Data analysis and machine learning materials

Analysis of the results of ILSVRC

Analysis of the results of the recently held ImageNet Large Scale Visual Recognition Challenge (ILSVRC), an annual image processing competition in which the Google team won first place.
MongoDb Data Modeling Guide

Not so long ago, Data Modeling Adviser for MongoDB was published on Daprota's website - a very useful guide to data modeling in the MongoDb NoSQL database.
AVITO.ru competition on Kaggle

The author tells about the experience gained while participating in the AVITO.ru competition on Kaggle and about the analysis of various approaches to solving the problem that other participants of the competition used.
A framework for constructing a dictionary when analyzing text

Continuation of a series of articles on text analysis and work with unstructured data. In this article, the author talks about possible approaches to solving the problem of constructing a dictionary when analyzing text data.
Improved image processing algorithms

A small article about the annual competition in image processing, in which the Google team won first place, having doubled the last year’s result.
Online course "Introduction to Computational Finance and Financial Econometrics"

More recently, an online course has started on Coursera, which will be useful to those who are interested in statistics and the R programming language, as well as to those who are interested in using statistical methods in the financial sphere.
On linear regression in simple language

A brief introduction to linear regression written in a fairly simple language.
Stinger.next: Improved SQL with Hadoop and Hive

An article from Hortonworks' blog about plans for the new product Stinger.next, which will significantly improve many of the qualitative indicators of the performance of SQL queries when working with Hadoop.
Using graph database for text analysis

An example of using the graph database Neo4j and Graphify to classify text using the Deep Learning algorithm.
Slides from the conference KDD 2014

Slides of several performances from KDD 2014.
Introduction to Machine Learning Studio for Microsoft Azure ML

This article tells about Machine Learning Studio, which allows you to work with the new cloud product for machine learning Microsoft Azure ML.
Deep Learning at Google

A small news article about Google’s progress in machine learning, Deep Learning. The article does not address the technical details of the implementation of the Deep Learning algorithms.
ShinyTree: jsTree + shiny

A short visualization example using the shinyTree library for the R programming language and the jsTree JavaScript library.
Creating an Excel Document Using Python and Pandas

Sample code that demonstrates how to create an Excel document using the Python programming language and the Pandas library.
NoSQL Trends: August 2014

Current trends on the main NoSQL-systems from various sites of online recruitment (Indeed, SimplyHired).
My favorite graphics

The author of the article talks about several types of graphs, which allow you to simply and clearly visualize various types of source data.
Video lectures from the course “Big Data, Large Scale Machine Learning”

Video from the “Big Data, Large Scale Machine Learning” course, which was held in 2013 and lasted 14 weeks, with Yann LeCun and John Langford as the main instructors.
Sampling error and non-sampling error

A small article, well explaining the difference between two concepts: sampling error and non-sampling error.
Machine learning with R

The author of the blog MachineLearningMastery tells how to quickly start using machine learning algorithms in the R programming language.
A thrilling year for Apache Spark

A small article on how the popularity of the Apache Spark product has evolved over the past year.
How to translate MapReduce requests to Apache Spark

A useful article from the Cloudera blog about how to translate MapReduce requests into the increasingly popular Apache Spark and understand the difference between the concepts in these two approaches.
What is Big Data?

What is Big Data, more than 40 experts answer this question on the Berkley blog.
Evaluating the accuracy of a predictive model using R Caret

5 ways to assess the accuracy of the predictive model available in the Caret machine learning library for the R programming language, described by the author of the popular blog MachineLearningMastery.
Digest of the best materials Hadoop ecosystem

Collection of the best materials for August on the Apache Hadoop ecosystem from the blog of the company Cloudera.
Introduction to Predictive Analytics

The first part of a new series of articles from the portal insideBIGDATA, this time on the topic of Predictive Analytics.
Using Google Charts in R Markdown

A small article that gives an example of using Google Charts in R Markdown documents.
Who is Data Scientist?

Not a bad attempt, I think, to describe what Data Scientist does.
Using D3.js templates

The use of templates in the popular library of visualization D3 in the programming language JavaScript.
6 types of Data Scientist activities

An interesting article about 6 different activities that Data Scientist has to do in its daily work.
9 Tips for Choosing NoSQL Storage (Part 1)

The first part of a series of articles that tells how to make the right choice of NoSQL-storage.
High Performance Material Review

Weekly digest of the most interesting materials on high performance from the popular HighScalability portal
Apache Pig with Apache Spark

An interesting article from the Cloudera blog about using Apache Pig with Apache Spark.
Cumulative frequency diagram in R

An example of constructing a cumulative private diagram using the R programming language and the ggplot2 library.
Image Analysis with EBImage

An example of working with images using the R programming language and the EBImage library.
5 ways to create two-dimensional diagrams in R

5 examples of creating two-dimensional diagrams using the programming language R.
A few words about the "linear" regression

An interesting article on linear regression with examples in the R programming language.
Work with MongoDb from R

A useful and very relevant article on how to work with MongoDb from the R programming language with NoSQL.
Machine Learning and Data Analysis Newsletters

It is often difficult to keep track of all the news in data analysis and machine learning. The author of the popular blog MachineLearningMastery offers a small list of newsletters that can simplify the task of getting the latest news from the field of Data Science.
Notifications in R

An example of code that will allow to receive notifications when the script in the R programming language has ended.
Error notifications in R

Another code example that allows sending notifications in case of errors when executing a script in the R programming language.
Statistical simulation vs machine learning

An interesting comparison of statistical modeling and machine learning.
Neural networks step by step

A good illustrated example of how a neural network works.
Interesting datasets

Several different datasets from social media with a small description of each.
Example of decision tree implementation

An example implementation of a decision tree in the programming language Python.