jackfrued / Python-100-Days
Python - 100天从新手到大师
jackfrued / Python-100-Days
NirDiamant / RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
ajcr / 100-pandas-puzzles
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
rasbt / LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
microsoft / ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
microsoft / Data-Science-For-Beginners
10 Weeks, 20 Lessons, Data Science for All!
fastai / fastai
The fastai deep learning library
fastai / fastbook
The fastai book, published as Jupyter Notebooks
NirDiamant / GenAI_Agents
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
norvig / pytudes
Python programs, usually short, of considerable difficulty, to perfect particular skills.
AccumulateMore / CV
✅（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】
spmallick / learnopencv
Learn OpenCV : C++ and Python Examples
NirDiamant / agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
mahmoud / awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
microsoft / mcp-for-beginners
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
alphacep / vosk-api
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
ageron / handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
jpmorganchase / python-training
Python training for business analysts and traders
AkashSingh3031 / The-Complete-FAANG-Preparation
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
yidao620c / python3-cookbook
《Python Cookbook》 3rd Edition Translation
aimacode / aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
GoogleCloudPlatform / python-docs-samples
Code samples used on cloud.google.com
NirDiamant / Prompt_Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
h2oai / h2o-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
cantaro86 / Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
charliedream1 / ai_quant_trade
Stock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code. 股票AI操盘手：一站式学习、模拟、实盘平台。涵盖：股票基础、策略、大模型、因子挖掘、机器学习/深度学习/强化学习、图网络、高频交易、C++部署及聚宽代码。
rasbt / reasoning-from-scratch
Implement a reasoning LLM in PyTorch from scratch, step by step
AnswerDotAI / nbdev
Create delightful software with Jupyter Notebooks
realpython / materials
Bonus materials, exercises, and example projects for our Python tutorials
py-why / EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
AllenDowney / ThinkDSP
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
microsoft / FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
mongodb-developer / GenAI-Showcase
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
AllenDowney / ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
bragai / bRAG-langchain
Everything you need to know to build your own RAG application
hemansnation / AI-Engineer-Headquarters
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
girafe-ai / ml-course
Open Machine Learning course
Visualize-ML / Linear-Algebra-Made-Easy---Learn-with-Python-and-Visualization
”数学不难“ 之 《线性代数不难》上下册，66话题完册；欢迎批评指正
matheusfacure / python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
MAIF / shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
pinecone-io / examples
Jupyter Notebooks to help you get hands-on with Pinecone vector databases
x4nth055 / pythoncode-tutorials
The Python Code Tutorials
szcf-weiya / ESL-CN
The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。
AllenDowney / ThinkPython
Jupyter notebooks and other resources for Think Python by Allen Downey, published by O'Reilly Media.
ipython / ipyparallel
IPython Parallel: Interactive Parallel Computing in Python
apache / hamilton
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
googlecolab / colabtools
Python libraries for Google Colaboratory
milvus-io / bootcamp
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
Xilinx / PYNQ
Python Productivity for ZYNQ
Tanu-N-Prabhu / Python
This repository helps you learn Python and Machine Learning from scratch.
jamesturk / jellyfish
🪼 a python library for doing approximate and phonetic matching of strings.
ageron / handson-mlp
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.
AllenDowney / ThinkBayes2
Text and code for the second edition of Think Bayes, by Allen Downey.
shsarv / Machine-Learning-Projects
This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.
gboeing / osmnx-examples
Gallery of OSMnx tutorials, usage examples, and feature demonstrations.
stanfordmlgroup / ngboost
Natural Gradient Boosting for Probabilistic Prediction
fbaptiste / python-deepdive
Python Deep Dive Course - Accompanying Materials
csinva / imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
NirDiamant / Controllable-RAG-Agent
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
scikit-learn-contrib / MAPIE
A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.