Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
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Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
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
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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.
30 Day Vanilla JS Challenge
A curated list of awesome Deep Learning tutorials, projects and communities.
Helping you select a JavaScript framework - Todo apps for React.js, Angular, Vue and many more
TranslatedLearn step by step: Spring Boot, Spring Boot & Shiro, Spring Batch, Spring Cloud, Spring Cloud Alibaba, Spring Security & Spring Security OAuth2. Source code for the blog's Spring series: https://mrbird.cc
A complete daily plan for studying to become a machine learning engineer.
TranslatedQiangu's illustrated front-end tutorials, an extremely detailed knowledge base from beginner to advanced front-end. Learn front-end from scratch and become a refined and elegant front-end engineer.
Questions to ask the company during your interview
Translated:see_no_evil: Programmer job-hunting blacklist: be careful when changing jobs or becoming a technical co-founder. Updated with 有赞 (Youzan)
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.
A collection of awesome penetration testing resources and tools
List of 1000 JavaScript Interview Questions
30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Awesome-LLM: a curated list of Large Language Model
Useful resources for creating apps with Electron [SUBMISSIONS ARE TEMPORARILY PAUSED BECAUSE I'M TIRED OF REVIEWING LOW-QUALITY STUFF]
🧠 Laws, Theories, Principles and Patterns for developers and technologists.