The following notes represent a complete, stand alone interpretation of Stanford’s machine learning course presented by Professor Andrew Ng and originally posted ...
This glossary defines general machine learning terms as well as terms specific to TensorFlow. Below is a small selection of the most popular entries. You can access this ...
A free online version of the second edition of the book based on Stat 110, Introduction to Probability by Joe Blitzstein and Jessica Hwang, is now available here. Pri...
When you give customers advice that can help them save some money, they will pay you back with loyalty, which is priceless. Interesting fact: Fareboom users started spe...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Artificial Intelligence is spreading its wings almost everywhere. Starting from the businesses to even the agricultural fields, AI is powering the world in many ways than...
The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, n...
This article was written by Will Koehrsen. Reading through a data science book or taking a course, it can feel like you have the individual pieces, but don’t quite kn...
This article was written by James Le. Some examples of tasks best solved by machine learning include: Recognizing patterns: Objects in real scenes, Facial identities or f...
I am pleased to announce that my quantum simulator Qubiter (available at GitHub, BSD license) now has a native TensorFlow Backend-Simulator (see its class `SEO_simulator_...