Learn what is a sklearn pipeline, and the reasons why you should use them in your ML project. Two simple examples in Python are included.

Learn the Mini-Batch Gradient Descent algorithm, and some of the key advantages and disadvantages of using this technique. Examples done in Python.

Learn the Stochastic Gradient Descent algorithm, and some of the key advantages and disadvantages of using this technique. Examples done in Python.

Gain insight, and an intuition, for how Neural Networks learn. A worked example, covering each step in the learning procedure, is included.

Learn the Batch Gradient Descent algorithm, and some of the key advantages and disadvantages of using this technique. Examples done in Python.

Cross Entropy serves as a loss function, in the context of machine learning classification problems. Learn all about the Cross Entropy Loss here.