The Jupyter Notebook, previously known as the IPython Notebook, is a language-agnostic HTML notebook application for Project Jupyter. Jupyter notebooks are documents that allow for creating and sharing live code, equations, visualizations, and narrative text together. People use them for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Data Analytics Portfolio - EDA, Data Cleaning & Analysis projects
Comprehensive library of numerical methods implemented in Python. It includes solutions to various mathematical problems, detailed explanations of each method, illustrative examples, and comparisons with prominent scientific libraries like Numpy, Scikit-Learn, and SciPy.
Interactive Jupyter notebook that compresses images with Run-Length Encoding (RLE): before/after preview, RGB histograms, size saved and compression ratio.
Focus stacking software with an interactive GUI and Python API for advanced image processing workflows
Quantitative geopolitical risk dashboard tracking Iran-Israel conflict escalation via market signals, GDELT news analytics, and probabilistic portfolio regime guidance.
This project performs sentiment analysis and topic modeling on a dataset of COVID-19-related tweets. The project classifies tweets into positive, negative, and neutral sentiments while uncovering key topics discussed on Twitter.
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
DevContainerでJupyter Notebookを使用してCSVからGithubActionsの使用量を測定する
Workshop materials for machine learning for network intrusion detection on the Edge-IIoTset IoT/IIoT dataset.
Portfolio of Data Science, Machine Learning, and Statistical analysis projects implemented in Python and R.
Colourful tensor operation visuals for NumPy style arrays, built for notebooks, docs, and teaching shape transformations.
End-to-end credit card fraud detection on highly imbalanced data (0.17% fraud) — SMOTE, class weights, XGBoost, LightGBM, PR-AUC threshold tuning, SHAP explainability, served via FastAPI + Streamlit and Docker.
Payment analytics project: Success Rate trends, recurrent payment failures, error 3.02 analysis and customer impact using Python and Pandas.
Machine learning-assisted platform for patient intake, case prioritization and clinical workflow support.
End-to-end retail analytics in a 77-cell Jupyter notebook over 1,067,371 UCI Online Retail II transaction lines: nine-step cleaning audit, RFM segmentation cross-checked against K-Means, CLV estimation and cohort retention. Names 683 high-value accounts worth £1.69M that stopped ordering. IBM SkillsBuild x BharatCares capstone.
Streamline client workflows with lightweight, browser-based tools for scoring service ideas and tracking 30-day launch plans.
Upscale Nuke renders with DLSS 5 neural rendering via an experimental native plug-in for Windows RTX GPUs.
Structured Python reference as Jupyter notebooks: fundamentals, OOP, regex and type hints. Also on Kaggle.
Transform your Mac into a real-time cinematic hacker security operations dashboard screensaver with live system stats.
Generate structured image captions, detailed descriptions, and alt text using vision-capable AI models with this lightweight FastAPI service.
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release Today