100 Days Of Deep Learning

Linear regression implementation from scratch using NumPy and Scikit Learn both.

Introduction to Linear Regression. Derivation of Ordinary Least Square method.

Perceptron implementation from scratch using NumPy and Matplotlib. Dataset via Scikit Learn.

Review the Matrix maths needed with PyTorch Tensor to understand Neural Networks.

Perceptron implementation in Python from scratch using PyTorch and SkLearn.

Perceptrons are the building blocks of Neural Networks. How do Perceptrons work?

I uncover the maths behind McCulloch-Pitts Neuron and how it works with Logical functions.

What are the main components of a Neural Network? How does a neural network work?

What are the types and use cases of deep learning? What are basic components of a neural network?

This is the very first post of 100 Days Of Deep Learning. It contains how I am taking up this challenge.