The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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🧠 Train a 64M-parameter LLM from scratch in just 2h!
A collection of learning resources for curious software engineers
- read-articles
- programmer
- professional
- scalability
Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.
- interview-preparation
- internships
- jobs
- university
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.
Comprehensive Python Cheatsheet
- cheatsheet
- python
- reference
- python-cheatsheet
TranslatedLatest summary for 2025: technical interview questions from Alibaba, Tencent, Baidu, Meituan, Toutiao and others, along with answers and a compilation of analysis from expert question-setters.
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.
- machine-learning
- deep-learning
- deep-reinforcement-learning
- machine-learning-from-scratch
Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai
- artificial-intelligence
- cloud-ml
- computer-systems
- courseware
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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.
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
Machine Learning Engineering Open Book
- pytorch
- slurm
- large-language-models
- llm
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
- machine-learning
- machine-intelligence
- artificial-intelligence
- reinforcement-learning
A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.
Python Implementation of Reinforcement Learning: An Introduction
A curated list of awesome things related to Django
DeFi Developer roadmap is a curated Developer handbook which includes a list of the best tools for DApps development, resources and references!
Open Machine Learning Course
A collection of agent recipes, reference patterns, and vertical plugins built with Agent Development Kit (ADK)
- adk
- agents
- agent-samples
code for Data Science From Scratch book
"Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization.
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