Digest of articles on data analysis No. 3 (June 09, 2014 — June 22, 2014)

Good afternoon, dear readers.
2 weeks went by and it was time for our data analysis toolkit. Today's digest turned out great, and I confess that the honor itself was not mastered by everything that got into it. But since there is no friend to the taste and color, I decided to post the entire selection.
So, from today's collection you will learn about how to use data stores of various types in one project, see what big data a business can possess and how their analysis can help it. Also in our compilation there will be an article devoted to the FTCA algorithm, and there will also be material about comparisons of various machine learning algorithms.

Theory

• ABBYY FineReader (RU) text recognition
• Big data is all information that is measured and changed in time (EN)
  An article about what big data really is and why the old definitions are not appropriate.
• Descriptive, Prescriptive, and Predictive Analytics (EN)
  The article describes the three main types of analyst, and also compares them.
• Different approaches to the use of probabilities and the difference of results (EN)
  
• 4 examples of the characteristics of big data (EN)
  
• Modeling Data Warehouse
  A small note about the construction of HD.
• Watch for analysts (EN)
  An interesting visualization of what the data analyst should know.
• Clustering clients in telecom (EN)
  The article provides a case on the subject specified in the title, as well as his decision.
• The first law of data analysis (EN)
  Note that the correlation in the data does not imply a causal relationship.
• Congenital Big Data Bias
  The article gives examples of the fact that bias can be laid already during data collection.
• How to make money on machine learning (EN)
  An interesting article on how to monetize your machine learning and data analysis skills.
• License plate recognition in detail (RU)
• Machine learning is fun.
  A little introduction to machine learning
• 10 errors that could jeopardize your database
• 5 bugs in big data you know about
  Common mistakes that everyone knows about, but still make them
• What is digital marketing? (En)
• 10 data analysis tools
• Cloud Computing (EN)
  Cloud Computing Note
• Efficient processing of big data on a daily basis (EN)
• 70 repository sites with datasets for analysis
• 9 secrets you need to know in the field of statistics
  What you studied at the university, but forgot about it.
• Using external data (EN)
  A story about where you can apply external data about your organization, taken from different sources.
• About cats, dogs, machine learning and deep learning
  
• Deep learning using neural networks. Beginner's Guide. (En)
• Naive Bayes and Logistic Regression (EN)
  Comparison of two models
• Development of an architecture for machine learning for risk calculation (EN)
• Hierarchical Recognition (EN)
  The author tells how he decided to create a deep learning algorithm for analyzing articles from Wikipedia
• FTCA clustering algorithm (EN)
• Probabilistic Models: Sampling (RU)
• Solving a linear regression problem using the fast Hough transform (RU)

Literature

• Data Analytics with R: A hands-on approach (EN)
• Understanding Machine Learning: From Theory to Algorithms
• Analytics Across the Enterprise
• Journal of the Association for Information Science and Technology (EN)
• Three Big Data Blueprints (EN)
• A selection of interesting books on data analysis (EN)

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Practice using different tools

• Phylogenesis in R and Python
• Comparison of classification algorithms with Python and Plotly (EN)
  The IPython Notebook console, which compares the various classification algorithms from the scikit-learn package.
• DLib: Machine Learning Library
  DLib open source library for C ++ language, which contains a wide range of machine learning algorithms.
• Introduction to the use of TVI (EN)
• Visualization of bus stops with R (EN)
  A quick note on using rCharts
• Django and big data. Part 1 - Primary Keys (EN)
• Analysis of crime statistics with the Federal Reserve Bank of Glue and plotly (EN)
  The article is designed as an IPython Notebook console.

Educational videos

• YaC / m 2014: Electronic Commerce Data Processing Techniques

Various related articles

• Why sites do not tell the client what he really needs (RU)
• How data visualization can help in radiology (EN)
  An interesting article on how big data can be used by radiologists.
• BI self-service is a new analytics democracy
  Reasoning on the fact that the developers of BI systems and their users should work closely together.
• We use machine learning to solve our problems.
  Interesting ideas on where to take everyday machine learning data sets.
• What is better intuition or analysis? (En)
  Arguments about whether analytical systems can make the right decisions without human intervention.
• Semantic analysis as a helper for building exact models
  Reasoning how semantic analysis of the model can help to increase its accuracy.
• Prescriptive analytics: what the doctor ordered
• Big effects from big data (EN)
  Part of an interview with the author of the book Analytics in a Big Data World.
• Cloud and big data pose no threat to data warehouses.
  Reasoning author on the topic of why the clouds and big data will not crowd out the data warehouse
• Selection of interesting articles from the world of big data (EN)
  Some of these articles have already been in our collections, and some are not.
• How cross-cutting areas help an organization shape innovation.
  The reasoning of the author that the algorithms are applicable in some areas of knowledge, can lead to good results in others.
• Move away from deep learning and get some prediction
  A note that simply applying machine learning algorithms does not lead to the desired results and a more in-depth analysis of the problem must be carried out.
• IBM Watson: where and how are the capabilities of the supercomputer now used? (Ru)
• Developing a successful strategy for using big data in business
  8 points to help you apply big data in your business
• Why text analytics is so important to search
• Big data in sports (EN)
• How analytics can help a CIO become more customer-oriented
• 5 key big data challenges in the banking sector (EN)
• What is big data and when will it turn into smart data?
• How I started working with machine learning
  The author tells how he encountered machine learning and began to apply it in his work.
• Business and Big Data: FABERNOVEL Laboratory (RU)
• Big data came to Russia. First projects
• How big data increases the efficiency of analytics in banks
• Who uses your data (EN)
• How big data can be applied when hiring staff
• How small businesses can leverage the power of big data
  A note that even a small business has big data, such as sales information, reviews in social networks, etc.
• Using different data warehouses (EN)
  A note on how to combine different types of data warehouses

activity

• Conference "Big Data for Biology and Medicine"