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

Resources

• New Data Science Cheat Sheet, by Maverick Lin 
• Tutorial: Exploratory Data Analysis …

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…

In this data science article, emphasis is on science, not just on data. State-of-the art material is presented in simple English, from multiple perspectives: applications, theoretical research asking more questions than it answers, scientific computing, machine learning, and algorithms. I attempt here to lay the foundations of a new statistical technology, hoping that it will plant the seeds for further research on a topic with a broad range of potential applications. It is based on…

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

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

Resources

• Python machine learning libraries 
• Tutorial: Statistical Tests of Hypothesis …

Over 1,000,000 machine learning, AI, analytics and data science practitioners use our resources. Access high quality, relevant and proprietary content found nowhere else. Find solutions to your problems, or learn how to transition to a career in data science.…

Here we describe a simple methodology to produce predictive scores that are consistent over time and compatible across various clients, to allow for meaningful comparisons and consistency in actions resulting from these scores, such as offering a loan. Scores are used in various contexts, such as web page rankings in search engines, credit score, risk score attached to loans or credit card transactions, the risk that someone might become a terrorist, and more. Typically a score is a function…

It all depends on the classes that you attended. Some are worth listing, some are best not to mention. Here I review of few of these data science curricula, and the impression it can make on hiring managers, depending on your profile, work experience, and strength (or lack of) of these programs.

Three…

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 technical resources posted since Monday. Enjoy the reading!

Resources

• A Plethora of Original, Not Well-Known Statistical Tests 
• 31 Statistical Concepts…

Many of the following statistical tests are rarely discussed in textbooks or in college classes, much less in data camps. Yet they help answer a lot of different and interesting questions. I used most of them without even computing the underlying distribution under the null hypothesis, but instead, using simulations to check whether my assumptions were plausible or not. In short, my approach to statistical testing is model-free, data-driven. Some are easy to implement even in Excel. Some of…

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…

This is an unusual application of AI, it is not fiction, and it works! It started probably more than 30 years ago. Sometimes referred to as symbolic mathematics, and usually relying on high performance and high precision computing, it aims at automatically solving or computing, with an exact solution (not an approximation) complicated…

With the two most recent ones, in this CRC series, published in January 2019. 

The objective of the series is to provide high-quality volumes covering the state-of-the-art in the theory and applications of statistical methodology. The books in the series are thoroughly-edited and present comprehensive, coherent and unified summaries of specific methodological topics from statistics. The chapters are written by the leading researchers in the field, and present a good balance of theory…

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

Technical

• Gambler's Ruin simulations 
• A Blast from Python Past - Part 2 …

The following articles were hand-picked, and curated by one of our interns. They cover dozens of topics of interest to data scientists. 

• Precision vs significance / accuracy vs precision / bias vs variance 
• Statistical Mistakes and How to Avoid…

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…

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…