The future is here and companies that have incorporated the latest innovations led by AI in their business processes are reaping the rewards. 

A full-stack AI strategy is the way forward and is being adopted by numerous organizations with their eyes on the…

Hello Everyone, I've just recently joined this site. Firstly, I would like to share with you all a free and open-sourced tool that I have published on github.com for Tableau that reduces the time required to complete a report. It takes the stress out of remembering what calculated fields are used and where across your workbook by giving you an easy to browse Tableau report that can be refreshed anytime…

By Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. Dated June 24, 2019. This is not the same book as The Math of Machine Learning, also published by the same department at Berkeley, in 2018, and also authored by Garret…

Every industry in the world is moving towards data-driven decision making, then one of the most popular and …

Nowadays, industries are privileged by the opportunity to apply data science to reach new heights in their efficiency, productiveness, and overall success. The range of these opportunities is pervasive starting with advanced calculations for the business to customer service…

I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie with p-values. Many applications (including the data…

This online book is intended for beginners, college students and professionals confronted with statistical analyses. It is also a refresher for professional statisticians. The book covers over 600 concepts, chosen out of more than 1,500 for their popularity. Entries are listed in alphabetical order, and broken down into 18 parts. In addition to numerous illustrations, we have added 100 topics not covered in our online series Statistical Concepts Explained in Simple English. We also…

Decision Trees, Random Forests and Boosting are among the…

You may have figured out already that statistics isn't exactly a science. Lots of terms are open to interpretation, and sometimes there are many words that mean the same thing—like "mean" and "average"—or sound like they should mean the same thing, like significance level and confidence level.  

Although they sound very similar, significance level and confidence level are in fact two completely different concepts. Confidence levels and confidence…

Introduction

Co-relation does not equal causation – is a mantra drilled into a Data Scientist from an early age

That’s fine ..

But very few talk of the follow-on question ..

How exactly do you determine causation?

This problem is…

Summary:  Based on a McKinsey study we reported that 47% of companies had at least one AI/ML implementation in place.  Looking back at the data and the dominance of RPA as the most widely reported instance makes us think that the number is probably significantly lower.

We’ve been trying to get a handle 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

• Earn a Data…

This article was written by Soft Media Lab.

It has the following sections.

Contents

• What is Machine Learning?
• How to apply machine learning to…

According to Wikipedia, an ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and can signal neurons connected to it.

In ANN implementations, the "signal" at a connection is a real number, and the output of each neuron is computed by some…

They say that the best ideas sometimes come to you while you are in the shower, and this idea of how to explain two important Neural Network concepts – Backpropagation and Stochastic Gradient Descent – actually did come to me as I was trying to set the perfect water temperature for my morning shower.

As I was struggling to adjust the two shower handles – one handle that controlled scolding hot and the other handle that controlled flash freezing – it occurred to me that I was a simple…

With intense urbanization, the transportation industry works round the clock to suffice the demands of…

Overview of changes TensorFlow 1.0 vs TensorFlow 2.0

Earlier this year, Google announced TensorFlow 2.0, it is a major leap from the existing TensorFlow 1.0. The key differences are as follows:

Ease of use: Many old libraries (example tf.contrib) were removed, and some consolidated. For example, in TensorFlow1.x the model could be made using Contrib, layers, Keras or estimators, so many options for the same task confused many new users.…