python-prep.md

Python preparation

General Programming

YouTube Playlists: PythonSocratica

1. Object Oriented Programming :

   • classes and objects
   • special functions examples and uses - __init__, __add__, __repr__, __call__
   • self keyword

2. Function Wrappers:

   • defining functions within functions
   • lambda functions, filter, map, reduce
   • passing functions as another function parameter *args and **kwargs

3. Files:

   • basic file i/o
   • open context manager

4. Libraries:

   • collections - useful data structures
   • pickle - saving data
   • json - dumping and loading JSON data
   • copy - create deepcopies (copy by value) for non-primitive and custom data types

5. Web:

   • requests library
   • familiarity with http/https and different type of requests that can be made

Data Analysis and ML

Courses to follow: CS231n Convolutional Neural Networks for Visual Recognition by Stanford University (YouTube)

1. Libraries:

   • basic ML - scikit-learn
   • computation - numpy
   • data manipulation - pandas
   • plotting - matplotlib and seaborn
   • image manipulation - python-opencv (import cv2)

2. Data Visualization:

   • Automatic profiling - pandas-profiling

3. Frameworks:

   • tensorflow/keras
   • pytorch/FastAI

4. Code Habits:

   • modular code
   • creating generators for datasets
   • defining train and test functions

5. Mathematical Concepts:

   • Singular Value Decomposition
   • Principal Component Analysis

6. Basic Web Scraping:

   • Beautiful Soup (from bs4 import BeautifulSoup)
   • able to collect iamges and training data using automated scripts

7. Basic DBMS:

   • SQL Programming
   • python libraries used to handle SQL databases

Data Structures and Algos

Courses to follow - Introduction to Algorithms by MIT (YouTube)

1. Data Structures:

   • deques (from collections import deque)
   • heaps and priority queues (from heapq import heapify, heappush, heappop)

2. Custom Structures:

   • nodes
   • linked lists
   • trees
   • graphs

3. Additional Resources:

   • CP Handbook/CLRS
   • YouTube video for graphs

NOTE - Try implementing every graph theory algorithm from the video in Python

4. Frequently asked:
   • Dynamic Programming
   • Greedy Algorithms
   • Stacks and Queues
   • Binary Trees and Graphs - inorder, preorder and postorder traversal of binary trees

Advanced Python Programming

Amazing Video: PyData Seattle 2017

1. Concepts:
   • context manager - yield keyword
   • generators - extremely important in ML, dataset creation (learn about __iter__ and __next__)
   • iterators and iterables
   • decorators - very powerful concept
   • metaclasses - uses and usage (optional)
   • threading and multiprocessing - perform multiple tasks concurrently
   • sockets and locks - access to database denied when something is being written