# Day 0: Announcement and Plan

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

May 24, 2021

**Objective?**

The goal is to blog every day about Deep Learning without a miss.

This is the very first post of 100 Days of Deep Learning and this blog. I have decided to post daily a blog for 100 days on Deep Learning from basic topics to advanced topics. It will be covering theory, maths, implementation, reading research papers and projects. The goal is to post a blog each day covering these without missing a single day.

**What's the plan?**

I know it is not possible to capture the whole *Deep Learning Vertical* in 100 days, unfortunately not even in 1000 days. I will try to be more general starting from basic going to advanced topics. Once we will be in the later phase we will start picking research papers as well. Each topic will be covered with theory as well as some maths if required.

At the end of this journey, we should have a good understanding of practical Deep Learning.

**When?**

I will be taking the first step and publishing the first blog on1st June 2021.

**Course Outline (WIP) :**

**Basic Maths / Preliminaries / Additional topics**- Data Processing and Manipulation
- Matrix Multiplication

- Calculus
- Distances
- Norms
- Gradient Descent
- SGD from scratch

- Backpropagation
- Linear Neural Networks
- Linear Regression, Implementation from scratch
- Softmax Regression

- Data Processing and Manipulation
**Deep Learning**- Artificial Neural Networks (ANN)
- Multilayer Perceptron
- Parameter Tuning
- How to approach a deep learning problem

- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- Generative Adversarial Networks (GAN)

- Artificial Neural Networks (ANN)
**Research Papers**- Reading and Understanding
- Implementation

**Projects**- Scope & Planning
- Implementation

**Case Studies**

Prerequisites

Prerequisites

These should be enough to get you going:

- Python with Numpy & Pandas
- Basic Linear Algebra and Calculus
- Matrix Multiplication
- Coding environment