We will dive into some weight initialization techiniques and how each one is good or bad

Why are activation functions important and how different activation functions are used in different types of problem statements and why are they used?

What is Unsupervised pretraining and how it opened doors for different researches in Deep Learning ?

A clear, intuition-first guide to why machine learning models overfit and how regularization techniques help them generalize better.

This blog gives you the understanding of What is bias , what is variance , and how training a model is doing a tradeoff between bias and variance.

This is a walk through my incomplete but amazing journey learning RL.

Deep dive into Backpropagation

A journey through the origins of neural networks, from the McCulloch-Pitts neuron to the Perceptron learning algorithm

Understand GD and its different varients