Here is our selection of featured articles, resources and forum questions posted since Monday:

Technical Resources

• Free Book: Foundations of Data Science (from Microsoft Research Lab) 
• Deep Learning…

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

Announcements

• Machine…

This is another spectacular property of the exponential distribution, and also the first time an explicit formula is obtained for the variance of the range, besides the uniform distribution. It has important consequences, and the result is also useful in applications.

Theorem

The range R(n) associated with n independent random variables with an exponential distribution of parameter l…

Here is our selection of featured resources and articles posted since Monday:

Resources

• Free Book: Classification and Regression In a Weekend 
• New book: Advanced Data Structures and Algorithms…

By Ajit Jaokar and Dan Howarth. With contributions from Ayse Mutlu.

Exclusively for Data Science Central members, with free access. You can download this book (PDF) here. 

This tutorial began as a series of weekend workshops created by Ajit Jaokar and Dan Howarth. The idea was to work with a specific (longish) program such that we explore as much of it…

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

Announcements

• Maximize…

Here is our selection of featured articles and technical resources posted since Monday.

Resources

• Confidence Intervals Without Pain, With Excel 
• The Lifecycle of Data …

We propose a simple model-free solution to compute any confidence interval and to extrapolate these intervals beyond the observations available in your data set. In addition we propose a mechanism  to sharpen the confidence intervals, to reduce their width by an order of magnitude. The methodology works with any estimator (mean, median, variance, quantile, correlation and so on) even when the data set violates the classical requirements necessary to make traditional statistical techniques…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

Announcements

• Earn a…

This crash course features a new fundamental statistics theorem -- even more important than the central limit theorem -- and a new set of statistical rules and recipes. We discuss concepts related to determining the optimum sample size, the optimum k in k-fold cross-validation, bootstrapping, new re-sampling techniques, simulations, tests of hypotheses, confidence intervals, and statistical inference using a unified, robust, simple approach with easy formulas, efficient…

Here is our selection of featured articles and resources posted since Monday:

Resources

• The Mathematics of Forward and Back Propagation 
• The Approximation Power of Neural Networks (with…

These 25 queries using our own data science search engine, return hundreds of articles and resources, sorted by popularity and recency. This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, …

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  

Announcement…

Here is our selection of featured articles and resources posted since Monday:

Resources

• Some Fun with Gentle Chaos, the Golden Ratio, and Stochastic Number Theory 
• Frequencies in Pandas Redux …

So many fascinating and deep results have been written about the number (1 + SQRT(5)) / 2 and its related sequence - the Fibonacci numbers - that it would take years to read all of them. This number has been studied both for its applications (population growth, architecture) and its mathematical properties, for over 2,000 years. It is still a topic of active research.…

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…

Here is our selection of featured articles and resources posted since Monday:

Resources

• Free Python Data Science coding Book series 
• Understanding Greedy Classifiers with a Real-World…

This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…