Note that it isn’t exactly trivial for us to work out the weights just by inspection alone. Many machine learning models allow some randomness in model training. Specifying a number for random_state ...

For supplementary readings, with each lecture, we will have pointers to either online reference materials, or chapters from the following books: CB: Pattern Recognition and Machine Learning, ...

1. Get the right Data Set: Need a right dataset to develop a model that can predict. 2. Understand the Dataset: Understand each feature / column and it's importance. 3. Choose the Depedent variable to ...

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems ...

This course gives a basic introduction to machine learning (ML) and artificial intelligence (AI). Through an algorithmic approach, the students are given a practical understanding of the methods being ...

Need to understand machine learning (ML) basics? This guide tells you how to plan for and implement ML in your devices. This essential intro to ML highlights strategy and best practices from the ...