The digest of articles on data analysis No. 3 (06/09/2014 - 06/22/2014)
Good afternoon, dear readers.
2 weeks have passed and the time has come for our selection of data analysis materials. Today’s digest turned out to be big, and I admit honestly I’ve mastered not everything that got into it. But since there is no companion for taste and color, I decided to lay out the entire selection.
So, from today's selection you will learn how to use data warehouses of various types in one project, look at how big data a business can possess and how their analysis can help it. Also in our selection there will be an article devoted to the FTCA algorithm, as well as material on comparing various machine learning algorithms.
Theory
- Text recognition in ABBYY FineReader (RU)
- Big data is all the information that is measured and changes over time (EN)
An article about that same thing to actually represent a big data and why the former definition unsuitable. - Descriptive, Prescriptive, and Predictive Analytics (EN)
The article provides descriptions of the three main types of analytics, as well as their comparison - Different approaches to using probabilities and difference in outcome (EN)
- Example 4 large data characteristics (EN)
- Modeling a data warehouse (EN)
A small note about building a hard disk. - Watch for analysts (EN)
An interesting visualization that needs to know a specialist in data analysis. - Clustering Clients in Telecom (EN)
The article provides a case on the topic specified in the title, as well as its solution. - First Law of Data Analysis (EN)
Note that correlation in data does not imply causation. - Congenital Big Data Bias (EN)
The article gives examples of how bias can be built into data collection. - How to make money on machine learning (EN)
An interesting article on how you can monetize your skills of machine learning and data mining - Car license plate recognition in detail (RU)
- Machine Learning is Fun (EN)
A small introduction to machine learning - 10 mistakes that can jeopardize your database (EN)
- 5 errors in large data that you know (EN)
Common mistakes which everyone knows, but still allow them - What is digital marketing? (EN)
- 10 tools for data analysis (EN)
- Cloud computing (EN)
place on introduction in the cloud - Efficient processing of large data on a daily basis (EN)
- 70 sites repository with data sets for analysis (EN)
- 9 secrets you need to know in the field of statistics (EN)
The fact that you have been taught at the university, but forgot about it. - Use 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 (RU)
- Deep learning using neural networks. Beginner's Guide. (EN)
- Naive Bayes and Logistic Regression (EN)
Comparison of two models - Architecting a machine learning system to calculate the risks (EN)
- Hierarchical Recognition (EN)
The author talks about how he decided to create a deep learning algorithm for analyzing articles from Wikipedia - Clustering algorithm FTCA (EN)
- Probabilistic Models: Sampling (RU)
- Solving the linear regression problem using the fast Hough transform (RU)
Literature
- Analytics with R Data: A hands-on approach (EN)
- Understanding Machine Learning: From Theory to Algorithms (EN)
- For Across the Enterprise Analytics (to EN)
- Association of the Journal for Science and Technology Information Part (to EN)
- Big the Data Blueprints the Three (to EN)
- A selection of interesting books on data analysis (EN)
The practice of using various tools
- Phylogeny in R and Python (EN)
- Comparison of classification algorithms with Python and Plotly (EN)
Console IPython Notebook, which compares different classification algorithms from scikit-learn package. - DLib: a machine learning library (
DL ) DLib is an open source library for the C ++ language that contains a wide range of machine learning algorithms. - Introduction to the use of the TVI (to EN)
- Visualization of bus stops using R (EN)
A small note on the use of rCharts - Django and big data. Part 1 - Primary keys (EN)
- Analysis of criminal statistics FRB with Glue and plotly (EN) The
article is designed as an IPython Notebook console
Educational videos
Miscellaneous Related Articles
- Why sites do not tell the client what he really needs (RU)
- As data visualization can help in radiology (EN)
An interesting article on how much data can be used by radiologists. - Self-service BI - the new democracy in analytics (EN)
The argument on the fact that the developers of BI systems and users must work closely together. - Use machine learning to solve their problems (EN)
Interesting ideas about where you can take data sets for machine learning in everyday life - What is better intuition or analysis? (EN)
Discussions about whether analytical systems can make the right decisions without human intervention. - Semantic analysis, as an assistant to construct accurate models (EN)
The arguments about how semantic analysis model can help to increase its accuracy. - Prescriptive Analytics: what the doctor ordered (EN)
- Large effects from large data (EN)
Part of an interview with the author of the book «Analytics in a Big Data World» . - Cloud and big data does not pose a threat to data warehousing (EN)
The reasoning of the author on why cloud and big data will supersede the data warehouse - A 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. - As the overlapping areas helps organizations to generate innovation (EN)
The arguments of the author that the algorithms are applicable in certain areas of expertise, can lead to good results in others. - Depart from deep learning and get some forecast (EN)
Note that simply using machine learning algorithms will not lead to the desired results and a deeper analysis of the problem should be carried out. - IBM Watson: Where and How Are Supercomputer Features Used Now? (RU)
- We are developing a successful strategy for using big data in business (EN)
8 points that will help you apply big data in your business - Why text analytics is so important to find (EN)
- Big data in the sport (EN)
- As an analyst can help CIOs to become more customer-oriented (EN)
- 5 key challenges of large data in the banking sector (EN)
- What is big data and when they become intelligent data (EN)
- How I started working with machine learning (EN)
The author talks about how he encountered machine learning and began to apply it in work. - Business and Big Data: FABERNOVEL Lab (RU)
- Big data came to Russia. First projects (RU)
- How big data analytics to increase the effectiveness of banks (EN)
- Who uses your data ?
- How much data can be used in the recruitment of personnel (EN)
- How small businesses can use the power of big data (EN)
A note that even small businesses have big data, such as sales information, reviews on social networks, etc. - Using different data storages (EN)
place on how to combine different types of data repositories