Machine Learning

What is Supervised Learning?

Supervised learning algorithms explained with the help of concrete examples and applications.

Support Vector Machines explained with examples, including kernel trick and advantages and disadvantages of using them.

Functionality of the Integrated Gradient explained using the example of a sentiment analysis.

Explanation of Recurrent Neural Networks, including definition, applications, types, and problems.

Introduction to the backpropagation algorithm with explanation of the gradient method and error backpropagation.

Learn how Convolutional Neural Networks use three-dimensional data for image classification and object recognition.

Linear regression basics, definitions and examples.

Gradient method explained with examples, learning rate and problems of gradient descent.

Artificial neural networks simply explained, including building blocks, layer types, and examples.