AtharvKhonde's Stars
binhnguyennus/awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
ashishps1/awesome-system-design-resources
Learn System Design concepts and prepare for interviews using free resources.
AtharvKhonde/PatternRecognitionOfStockChart
ashishps1/awesome-behavioral-interviews
Tips and resources to prepare for Behavioral interviews.
iam-veeramalla/aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days. This repo includes projects, presentations, interview questions and real time examples.
jobream/Leetcode-Company-Wise-Problems
This is a repository containing the list of company wise questions available on leetcode premium. Every pdf file in this repository corresponds to a list of questions on leetcode for a specific company based on the leetcode company tags.
openai/gym
A toolkit for developing and comparing reinforcement learning algorithms.
khanhnamle1994/movielens
4 different recommendation engines for the MovieLens dataset.
kishan0725/The-Movie-Cinema
The Movie Database for all language movies
MilovanTomasevic/iOS-Swift-The-Complete-iOS-App-Development-Bootcamp
From Beginner to iOS App Developer with Just One Course! Fully Updated with a Comprehensive Module Dedicated to SwiftUI!
derekbanas/Python4Finance
I get many questions about how to analyze the Stock Market with Python. I am creating a new playlist of videos that will completely cover Python for Finance.
vdespa/introduction-to-postman-course
Kennygunderman/snack-chat
A chatting app focused on real-time data sync using firebase | Built with Flutter
WongKinYiu/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
muratali016/Yolov7-Object-Counter-Custom-Funcitons
Object Counting with the newest yolov7
mml-book/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
zotroneneis/machine_learning_basics
Plain python implementations of basic machine learning algorithms
vbartle/MML-Companion
This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Faisal and Cheng Ong, written in python for Jupyter Notebook.
firstcontributions/first-contributions
🚀✨ Help beginners to contribute to open source projects
github/opensource.guide
📚 Community guides for open source creators
ossu/computer-science
🎓 Path to a free self-taught education in Computer Science!