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 Data…

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

Resources

• TensorFlow 1.x vs 2.x. – summary of changes
• The problem that Google Solved with Quantum Supremacy…

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…

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

Announcements

• Deep Learning and AI For All - eBook
• Democratizing Data Analytics and AI - Sep 25
• Migrating R Applications to the Cloud using Databricks - Sep 26…

I am presenting at the upcoming NISS (National Institute of Statistical Sciences) webinar on September 27. This was my first employer in US, back in 1996. I was then completing a post-doc.

My presentation focuses on new algorithms, original applications, theoretical data science (including a new conjecture about data sets) and implications to business analytics, as well as new foundations of statistics, based on general resampling and model free, data-driven techniques. It will also…

Guest blog post by Nabanita Roy.

Introduction:

The art and science of discriminating between writing styles of authors by identifying the characteristics of the persona of the authors and examining articles authored by them is called Authorship Analysis. It aims to determine characteristics of an individual like age, gender, native language and personality traits…

Guest blog post by Nabanita Roy.

Introduction:

The art and science of discriminating between writing styles of authors by identifying the characteristics of the persona of the authors and examining articles authored by them is called Authorship Analysis. It aims to determine characteristics of an individual like age, gender, native language and personality traits…

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

• Building…

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

Announcement

• Migrating R Applications to the Cloud - Upcoming Webinar

Technical Contributions

• The…

This is an interesting data science conjecture, inspired by the well known six degrees of separation problem, stating that there is a link involving no more than 6 connections between any two people on Earth, say between you and anyone living (say) in North Korea.   

Here the link is between any two univariate data sets of the same…

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.

• Find your…

The material discussed here is also of interest to machine learning, AI, big data, and data science practitioners, as much of the work is based on heavy data processing, algorithms, efficient coding, testing, and experimentation. Also, it's not just two new conjectures, but paths and suggestions to solve these problems. The last section contains a few new, original exercises, some with solutions, and may be useful to students, researchers, and instructors offering math and statistics classes…

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

Technical Resources

• Jobs, Unemployment and 45's Performance - Analysis done with Python
• Object Detection using Deep…

Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 variables, say with 10 observations. Compute all the (99,999 * 100,000) / 2 cross-correlations. You are almost guaranteed to find one above 0.999. This is best illustrated in may article How to Lie with P-values (also discussing how to handle…

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, ouliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, and many more. To keep receiving these articles, …

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, 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.  

Featured Resources and Technical…