Jupyter Notebooks
Showing 36 of 106 projects
An open-source threat hunting platform with advanced analytics capabilities built on ELK stack, Apache Spark, and Jupyter notebooks.
A collection of Jupyter notebooks accompanying a 10-part video series teaching machine learning with Python's scikit-learn library.
A collection of handwritten notes, notebooks, and resources for Andrew Ng's Deep Learning Specialization on Coursera.
A comprehensive lecture series teaching scientific computing with Python through interactive IPython notebooks.
A Python library that simplifies chart creation for data scientists with consistent data formats and smart defaults.
A Python library that simplifies chart creation for data scientists with consistent data formats and smart defaults.
The fastest way to build data pipelines with iterative development and deployment anywhere.
An easy-to-use blogging platform with enhanced support for Jupyter Notebooks, Word docs, and Markdown, powered by GitHub Actions.
A comprehensive collection of machine learning tutorials and implementations in Python, covering algorithms from scratch to production deployment.
Interactive HTML widgets for Jupyter notebooks, enabling dynamic data exploration and visualization.
A catalog of production-ready Jupyter Notebook templates organized by tools and following the IMO (Input, Model, Output) framework.
A collection of Python notebooks and tools for quantitative finance research, including backtesting, machine learning, and portfolio optimization.
An interactive online learning platform for computer vision with a comprehensive Chinese ebook, code, and community.
Docker image providing the Python environment used by Kaggle Notebooks for data science competitions.
A collection of Jupyter notebooks demonstrating how to use the Qiskit SDK for quantum computing.
A Python tutorial and cookbook for implementing Bayesian modeling techniques using PyMC3.
Automatically visualize any dataset with a single line of code, including data quality assessment and fixes.
A collection of interactive machine learning experiments with Jupyter notebooks for training and browser demos for visualization.
Python code and examples for Bayesian statistics from the book 'Think Bayes: Bayesian Statistics Made Simple'.
An accelerated machine learning framework for Go, offering a PyTorch/Jax/TensorFlow-like experience with support for CPUs, GPUs, TPUs, and WASM.
A web-based collaborative platform for research, teaching, and scientific publishing with Jupyter Notebooks, Sage Worksheets, LaTeX, and real-time collaboration.
A collection of Jupyter notebooks for financial economics, providing high-level APIs to retrieve, analyze, and visualize economic data from sources like FRED.
A Python library that provides direct, Pythonic access to Praat's speech processing algorithms from within Python.
Run Python linters and formatters like ruff, black, and mypy directly on Jupyter Notebooks.
A teaching platform providing interactive Jupyter Notebooks for learning computer-aided drug design (CADD) using open-source tools.
A curated list of tools, demos, and resources for scientific writing beyond LaTeX, including Markdown, Jupyter, and reference management.
A curated list of tools, demos, and resources for scientific writing beyond LaTeX, including Markdown, Jupyter, and reference management.
A Ruby kernel for Jupyter notebooks, enabling interactive data science and computational workflows in Ruby.
Learn statistics through Python with real-world examples like analyzing marijuana price data across US states.
A platform for creating and publishing dynamic, data-driven documents with built-in code execution and collaboration.
CVPR 2015 workshop materials for learning deep learning and computer vision with Torch framework.
A Clojure library for creating interactive data visualizations and scientific documents using Vega and Vega-Lite.
A collection of tutorials and resources to help developers learn JAX, Flax, and Haiku for machine learning.
A Nix-based framework for creating declarative and reproducible Jupyter environments with configurable kernels and extensions.
A collection of Jupyter notebooks providing examples and tutorials for the Bokeh interactive visualization library.
Capture, analyze, and transform messy Jupyter notebooks into production data pipelines with just two lines of code.
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