Pushkar Raj's repositories
julia_basics
This repository is all about Julia and nothing else.
awesome-web-scraping
List of libraries, tools and APIs for web scraping and data processing.
Beyond-LeetCode-SQL
Analysis of SQL Leetcode and classic interview questions. Common pitfalls, anti-patterns and handy tricks are discussed. Sample databases are provided.
CSV.jl
Utility library for working with CSV and other delimited files in the Julia programming language
DataFrames.jl
In-memory tabular data in Julia
dtype_diet
Tries to shrink your Pandas column dtypes with no data loss so you have more spare RAM
emoji-cheat-sheet
A markdown version emoji cheat sheet
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Impractical_Python_Projects
Code & supporting files for chapters in book
intro-to-apis-course
Introduction to APIs course
Julia-DataFrames-Tutorial
A tutorial on Julia DataFrames package
JuliaDB.jl
Parallel analytical database in pure Julia
jupyter-text2code
A proof-of-concept jupyter extension which converts english queries into relevant python code
learn-regex
Learn regex the easy way
math-worksheet-generator
Create basic addition, subtraction and multiplication practice questions with the answer sheet
Network-Analysis-Made-Simple
An introduction to network analysis and applied graph theory using Python and NetworkX
pyautogui
A cross-platform GUI automation Python module for human beings. Used to programmatically control the mouse & keyboard.
python-training
Python training for business analysts and traders
SQL-Leetcode-Challenge
Contains all the 117 Leetcode questions with their solutions ranging from Easy to Hard in MySQL.
twint
An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.
visualize-browser-history
Visualisation of browsing history patterns using pandas and seaborn