This repository contains .ipynb notebooks covering the Basics of Python along with Basics of ML and DL and is mainly meant to help students enrolled in various projects under TiP.

The repository has been divided into several repositories -:

1.Basic Python - Contains .ipynb files covering basics of python

2.Datasets - Contains necessary datasets used in the notebooks in the repository

3.Deep Learning-Examples - Contains .ipynb files covering the basics of Deep Learning

4.Exercise - Contains some problems based on the basic Python Libraries and Basic ML

5.Machine Learning Examples - Contains .ipynb files covering the basics of Machine Learning

Solutions to the exercises and more exercise notebooks will be added as we move further.

For more on Machine Learning, refer to -: http://cs229.stanford.edu/notes/

For more on Deep Learning, refer to -: http://cs231n.github.io/

NOTE-:The students are supposed to try the exercise after they compile the other notebooks and be a bit confident with programming in python and are familiar with the basics of Machine Learning.

The notebooks namely-MatplotlibExercises.ipynb and NumpyExercises.ipynb have been taken from -:

https://www.udemy.com/course/python-for-finance-and-trading-algorithms/

The notebooks namely-Basic_python.ipynb and NumPy_MatPlotlib.ipynb have been taken from -:

https://github.com/practicalAI/practicalAI/tree/master/notebooks/