Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
- agent
- claude-code
- teaching
- agent-development
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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
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
- deep-learning
- deep-learning-tutorial
- pytorch
- gan
🧠 Train a 64M-parameter LLM from scratch in just 2h!
Translated"Code Random Thoughts" (代码随想录) LeetCode problem-solving guide: the order for working through 200 classic problems, with 600,000 characters of detailed illustrated explanations, video analysis of difficult points, and over 50 mind maps. Supports multiple language versions including C++, Java, Python, Go, and JavaScript, so learning algorithms is never confusing again! 🔥🔥 Come take a look, and you will wish you had met it sooner! 🚀
TranslatedDive into LLMs: a series of hands-on programming tutorials
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
100 Days of ML Coding
- machine-learning
- machine-learning-algorithms
- infographics
- tutorial
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
- tensorflow
- tutorial
- examples
- deep-learning
TranslatedAiLearning: Data Analysis + Machine Learning in Action + Linear Algebra + PyTorch + NLTK + TF2
- fp-growth
- apriori
- mahchine-leaning
- naivebayes
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
What the f*ck Python? 😱
- python
- wats
- snippets
- wtf
Translated📚 Building large models from scratch
Translated"开源大模型食用指南" (Open-Source Large Model Usage Guide): a tutorial tailor-made for Chinese users on quickly fine-tuning (full-parameter/LoRA) and deploying domestic and international open-source large language models (LLM) and multimodal large models (MLLM) in a Linux environment
PyTorch Tutorial for Deep Learning Researchers
- deep-learning
- pytorch-tutorial
- neural-networks
- pytorch
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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.
TranslatedPython tutorial for beginners
- python
- python3
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
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TranslatedA Python web scraping tutorial series, learning Python web scraping from 0 to 1, including browser packet capture and mobile APP packet capture with tools such as fiddler and mitmproxy, the use of the various modules involved in web scraping, such as requests, beautifulSoup, selenium, appium, scrapy, etc., as well as IP proxies, CAPTCHA recognition, using Mysql and MongoDB databases with Python, multi-threaded and multi-process scraping, reverse engineering and cracking of CSS scraping encryption, JS scraping reverse engineering, distributed scraping, practical scraping project examples, etc.
- python3
- python-script
- python-spider
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.