Here is a simple trick that can solve a lot of problems. You can not trust a linear or logistic regression performed on data if the error term (residuals) are auto-correl...
The benefits of AI for healthcare have been extensively discussed in the recent years up to the point of the possibility to replace human physicians with AI in the futu...
This simple introduction to matrix theory offers a refreshing perspective on the subject. Using a basic concept that leads to a simple formula for the power of a matrix, ...
Azure Machine Learning concepts – an Introduction Introduction Last week, we launched a free book called Classification and Regression in a weekend. The idea of the...
Cross Validation explained in one simple picture. The method shown here is k-fold cross validation, where data is split into k folds (in this example, 5 folds). Blue ball...
Digital capabilities leverage customer, product and operational insights to digitally transform business models. And nowhere is this more evident than the rush by indus...
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...
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...
We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning.