1xiaolai / the-craft-of-selfteaching
One has no future if one couldn't teach themself.
Ranked by Attention Score: stars gained over the last 7 complete days
27 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
One has no future if one couldn't teach themself.
This is a repo with links to everything you'd ever want to learn about data engineering
Anthropic's Interactive Prompt Engineering Tutorial
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here 👇🏼
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
✅(已完结)超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
Learn ML engineering for free in 4 months! Register here 👇🏼
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/
高校生向けLLM教材: Karpathy microgptベース,Google Colab用
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版
Companion webpage to the book "Mathematics For Machine Learning"
💿 Free software that works great, and also happens to be open-source Python.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Course Files for Complete Python 3 Bootcamp Course on Udemy
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Learn OpenCV : C++ and Python Examples
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
Simple tutorials using Google's TensorFlow Framework
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Lectures on scientific computing with python, as IPython notebooks.
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission (CHIL 2020 Workshop)
This project aims to classify human activities using data obtained from accelerometer and gyroscope sensors from phone and watch.