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Lists of company wise questions. Every csv file in the companies directory corresponds to a list of questions on leetcode for a specific company based on the leetcode company tags. Updated as of 20 Oct, 2025
Algorithms and Data Structures implemented in JavaScript for beginners, following best practices.
The OWASP Cheat Sheet Series was created to provide a concise collection of high value information on specific application security topics.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Roadmap to becoming an Artificial Intelligence Expert in 2022
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A list of AI autonomous agents
This repository started out as a learning in public project for myself and has now become a structured learning map for many in the community. We have 3 years under our belt covering all things DevOps, including Principles, Processes, Tooling and Use Cases surrounding this vast topic.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
:memo: An awesome Data Science repository to learn and apply for real world problems.
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
100+ Python challenging programming exercises
If you want to become good at AI engineering & system design, join this newsletter 👇
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
A complete daily plan for studying to become a machine learning engineer.
Curated list of Go design patterns, recipes and idioms
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Learn Low Level Design (LLD) and prepare for interviews using free resources.
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
The Open Source Data Science Masters
280+ free n8n automation templates — ready-to-use workflows for Gmail, Telegram, Slack, Discord, WhatsApp, Google Drive, Notion, OpenAI, and more. AI agents, RAG chatbots, email automation, social media, DevOps, and document processing. The largest open-source n8n template collection.