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...
Summary: As the Automated Machine Learning (AML) movement got underway a few years back there was an early branch between proprietary platforms and open source platforms....
Like many emergency rooms in the United Kingdom, the A&E department at Salford Royal NHS Foundation Trust, Greater Manchester, faces high congestion. This results in ...
Are you struggling to bring about change in your organization? Is your team or company stuck in entrenched modes of behavior despite your awesome data visualizations? Wha...
I love watching the NBA’s Golden State Warriors play basketball. Their offensive “improvisation” is a thing of beauty in their constant ball movement in order to fi...
The following resources and books were hand-picked, and curated by one of our interns. They cover many topics of interest to data scientists, and most are relatively rece...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Most of us start working with specific programming languages like TensorFlow and Pyspark So, we are relatively not so used to working with Cloud APIs. But Cloud APIs for ...
A complete guide to K-means clustering algorithm Let’s say you want to classify hundreds (or thousands) of documents based on their content and topics, or you wish to�...
Summary: Communicating with your Board of Directors about AI/ML is different from conversations with top operating executive. It’s increasingly likely your Board wi...