Clean Code concepts adapted for JavaScript
- javascript
- principles
- composition
- inheritance
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Clean Code concepts adapted for JavaScript
Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
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, ... 🧠
📜 33 JavaScript concepts every developer should know.
100 Days of ML Coding
30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Learn regex the easy way
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TranslatedAiLearning: Data Analysis + Machine Learning in Action + Linear Algebra + PyTorch + NLTK + TF2
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
🤪 A list of funny and tricky JavaScript examples
Translated🥇Juejin Translation Project (掘金翻译计划, Gold Miner), possibly the largest and best English-to-Chinese technical translation community in the world, the translation platform that best understands readers and translators:
An interactive git visualization and tutorial. Aspiring students of git can use this app to educate and challenge themselves towards mastery of git!
PyTorch Tutorial for Deep Learning Researchers
TranslatedThe place where 冴羽 (Yu Saeba, "Saeba Yu") writes his blog; he plans to write four series: an in-depth JavaScript series, a JavaScript topics series, an ES6 series, and a React series.
How to create an OS from scratch
A playbook for systematically maximizing the performance of deep learning models.
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.
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
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
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.