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.
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
A jupyter notebook server via HEROKU web without Password.
A repository for sharing ipynb's of my experiments with ML. Some notebooks are 'old' by now and might no longer work 'out of the box'.
🗂 markdown tool to create table of content from jupyter notebooks
A simple command-line tool for converting Python scripts to Jupyter notebooks and vice versa.
✨ This repository is your go-to resource for seamlessly transforming Jupyter Notebook (ipynb) 📚 files into portable document format (PDF). 📚 🔀 It provides a simple and convenient way to convert Jupyter Notebook (ipynb) files to PDF format 🤓
This is a Data Science Africa 2023 entry notebook.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Writing PostgreSQL queries into jupyter notebook
IPython Notebook showing pytorch implementation of Google DeepMind paper on Relation Network
Computer vision fundamentals interactive Jupyter notebooks from Introduction to Computer Vision Udacity course and the Computer Vision Algorithms, Applications book 2nd Edition by Richard Szeliski and opencv trutorials.
Created as a demonstration to showcase the usefulness of RNN's with LSTM, in the pursuit of accurate stock price prediction models. Creating using Tensorflow. Written in Python-3 using Jupyter Notebook
Data Science Internship - IneuBytes Aug 2023 This repository contains my work and solutions for the Data Science Internship offered by IneuBytes in August 2023. It includes code, notebooks, and analyses for three distinct datasets provided as part of the internship.
Automated Tabular Data Extraction and Prediction is a Python project that combines image processing and machine learning for extracting and predicting tabular data from images with over 80% accuracy. Use this versatile solution by exploring the Jupyter Notebook, and seamlessly integrate it into your projects.
Contenido completo del curso
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release about 2 months ago