mrdbourke / zero-to-mastery-ml
Course materials, code, notebooks and datasets for the Zero to Mastery Machine Learning and Data Science course.
mrdbourke / zero-to-mastery-ml
microsoft / ML-For-Beginners
A 12-week, 26-lesson beginner curriculum on classic machine learning using Scikit-learn, with quizzes and projects in Python and R.
stefan-jansen / machine-learning-for-trading
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
GokuMohandas / Made-With-ML
A free course teaching how to design, develop, deploy, and iterate on production-grade machine learning applications in Python.
microsoft / Data-Science-For-Beginners
A 10-week, 20-lesson beginner curriculum teaching data science through project-based lessons with quizzes and assignments.
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
AllenDowney / ThinkStats
Notebooks for the third edition of Think Stats
fastai / fastbook
The fastai book, published as Jupyter Notebooks
AllenDowney / ElementsOfDataScience
An introduction to data science in Python, for people with no programming experience.
mahmoud / awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
lavine888 / CityU-CS-Notes
Course notes & materials based on my CityU MSc CS journey. Includes study notes from 10 courses and resources shared by peers. Hope it helps fellow students — Star & PRs welcome. 基于香港城市大学 MSc CS 修课经历整理的课程笔记与资料。收录 10 门课程的学习沉淀，以及课程社群中同学们分享的资料。希望能帮到同样在学的同学，欢迎 Star 与 PR。
KarryRen / SCU-CS-Class-Materials
四川大学计算机学院本科课程资料（更新中 🔥）如果您觉得有帮助，还请点亮一下 Star 🌟 哦~ 万分感谢！
petrobras / 3W
Timely detections for more proactive and effective actions in offshore oil wells!
fengdu78 / Data-Science-Notes
数据科学的笔记以及资料搜集
microsoft / FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
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.
cksystemsteaching / selfie
An educational software system of a tiny self-compiling C compiler, a tiny self-executing RISC-V emulator, and a tiny self-hosting RISC-V hypervisor.
scikit-learn-contrib / MAPIE
A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
jpmorganchase / python-training
Python training for business analysts and traders
evidentlyai / evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
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.
aeturrell / coding-for-economists
This repository hosts the code behind the online book, Coding for Economists.
joanby / python-ml-course
Curso de Introducción a Machine Learning con Python
d3blocks / d3blocks
The Python library to create stand-alone and interactive d3 charts.
makcedward / nlpaug
Data augmentation for NLP
tensorflow / probability
Probabilistic reasoning and statistical analysis in TensorFlow
AllenDowney / ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
matheusfacure / python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Azure / azureml-examples
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
gboeing / osmnx-examples
Gallery of OSMnx tutorials, usage examples, and feature demonstrations.
csinva / imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
nubank / fklearn
fklearn: Functional Machine Learning
NannyML / The-Little-Book-of-ML-Metrics
The book every data scientist needs on their desk.
divelab / AIRS
Artificial Intelligence Research for Science (AIRS)
AllenDowney / ThinkComplexity2
Book and code for Think Complexity, 2nd edition
wx-chevalier / AI-Notes
:books: [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记
pdpipe / pdpipe
Easy pipelines for pandas DataFrames.
google / edward2
A simple probabilistic programming language.
CornellNLP / ConvoKit
ConvoKit is a toolkit for extracting conversational features and analyzing social phenomena in conversations. It includes several large conversational datasets along with scripts exemplifying the use of the toolkit on these datasets.
cfgranda / ps4ds
Probability and Statistics for Data Science: A self-contained introduction to probability and statistics for data science, including a free pdf, 103 Python notebooks using 23 real-world datasets, 118 videos with slides, and solutions to 200 exercises
DataFabric-Academy / ms-fabric-data-science
Hands-on Microsoft Fabric Data Science labs (FreshMart churn) with Thai study notes, PySpark/MLflow, and DP-604-aligned learning path.
helvecioneto / datascience
Repositório para as aulas da disciplina SSIN0044 - INTRODUÇÃO À CIÊNCIA DE DADOS - T01 (Universidade Federal do Oeste do Pará)
aws / amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.