《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
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Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
- machine-learning
- models
- ui
- ui-components
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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.
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
- notebooks
- python
- data-science
- machine-learning
100-Days-Of-ML-Code中文版
- machine-learning
- python
- 100-days-of-ml-code
- chinese-simplified
Best Practices on Recommendation Systems
- machine-learning
- recommender
- ranking
- deep-learning
Generate audiobooks from e-books, 50+ TTS engines with voice cloning and 1696 languages!
Unofficial Python API and agentic skill for Google Gemini Notebook. Full programmatic access to Gemini Notebook's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.
- python
- sdk
- skills
- google-notebooklm
The interactive graphing library for Python :sparkles:
Air-gapped, privacy-focused, open-source NotebookLM alternative. AI agent that researches, transforms, and edits your documents. Join our Discord: https://discord.gg/ejRNvftDp9
100 numpy exercises (with solutions)
Draw pretty maps from OpenStreetMap data! Built with osmnx +matplotlib + shapely
- matplotlib
- jupyter-notebook
- python
- generative-art
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Ready-to-run Docker images containing Jupyter applications
Multi-user server for Jupyter notebooks
- jupyter-notebook
- jupyterhub
- python
- multi-user
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
- jupyter-notebook
- jupyterlab-extension
- version-control
- knitr
📚 Parameterize, execute, and analyze notebooks
- jupyter
- notebooks
- notebook-generator
- nteract
Voilà turns Jupyter notebooks into standalone web applications
- jupyter
- jupyter-notebook
- jupyterlab-extension
- dashboarding
An open source extension that connects AI agents to computational notebooks in JupyterLab.
Impress your boss and turn a Jupyter notebook into a beautiful, shareable web app — no callbacks, no frontend, no rewrite.
- notebook-jupyter
- notebooks-jupyter
- notebook-application
- notebook-publish
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
- machine-learning
- ml
- model-validation
- data-validation