Data is a unique economic asset; it never depletes, never wears out and can be used across an unlimited number of use cases at near zero marginal cost. Data in the hands ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Machine learning applications require powerful and scalable computing systems that can sustain the high computation complexity of these applications. Companies that are w...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
By Amita Kapoor and Ajit Jaokar. In this book, we introduce coding with tensorflow 2.0. We show how to develop with tensorflow 1.0 and contrast how the same code can be d...
Interesting analysis done in R, about salaries of R developers broken down by country, featuring salary range and median salary. The dataset consists of survey answer...
Last week I posted the first of a three-part series on basic data programming with Python. For that article, I resurrected scripts written 10 years ago that deployed co...
Summary: McKinsey says platform companies will represent 30% of global business revenue by next year (2020). In Part 1 of this article we started to lay out some impo...
Where will blockchain go in the coming new year 2020? We’re on the edge of 2019. Isn’t this a great time to make predictions about blockchain – a revolutionary tech...
At our meetup Data Science for Internet of Things, Dan Howarth conducted a workshop on tensorflow 2.0 we plan to convert it into another book on data science central. fo...