Python tutorials

Need to add:

1. Git and VSCode Tutorial First
2. Then add Basic Syntax
3. Control Flow
4. Functions and Scope
5. DS & A part I
6. DS & A part II
7. Concurrency and Parallelism in Python Part I
8. Advanced String Manipulation
9. File Handling
10. Iterators and Generators
11. Lambda Functions and Functional Programming
12. OOP Part I
13. Metaprogramming and Decorators
14. DS & A part III
15. Pandas, NumPy, Numba for optimisation and data presentation.

Details for Above

1. How to install Python.
2. How to setup VSCode.
3. Setup interpreter path.
4. Test program.
5. Git installation.
6. Basic Git commands (clone, push, pull, commit, branching)

ML for Python

• Mathematics for ML: Statistics, Vectors/Matrices and probability.
• Linear Regression Models
• Logistic Regression
• SVMs
• Random Forests, Gradient Boosting.
• Clustering methods.
• Neural Networks (Feed-Forward, Convolutional, Recurrent)
• Reinforcement Learning.