Path to Deep Learning

Step 1:

Basics of python

• variable assigning, functions, lists, tuples, set, dictionary, list comprehensions, list manipulations, etc

Step 2:

Algorithms and Data structure by interviewcake

• You can get it free if you apply for Github students pack. If you want to buy it then they are giving 75% discounts for the corona outbreak.

• WHY?

  	- Programming is not just coding but being able to solve problems as well.
  
  	- Better problem-solving ability will be a boost during learning data science.
  

Step 3:

Data Analysis

• Data cleaning, processing, analyzing and visualizing is a must for every Deep Learning expert.

• We will learn Numpy, Pandas, Matplotlib and seaborn.

Step 4 :

Deep Learning with Pytorch

• Learning PyTorch from very basic tensors to Generative adversarial network from freecodecamp Youtube videos taught by Jovian.ml

• Not tensorflow because their APIs and syntax keep changing so much that it becomes hard to keep track of.

• We shall learn sklearn, pandas and matplotlib as and when required alongside from their documentaion.

• If the quarrantine still remains, we shall move over to Kaggle and try some challenges.