Python Data Science Handbook: full text in Jupyter Notebooks
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Updated
Jun 26, 2024 - Jupyter Notebook
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.
Python Data Science Handbook: full text in Jupyter Notebooks
Repository to store sample python programs for python learning
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
100-Days-Of-ML-Code中文版
Jupyter Interactive Notebook
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch:入门与实战》)
Best Practices on Recommendation Systems
Ready-to-run Docker images containing Jupyter applications
The interactive graphing library for Python ✨ This project now includes Plotly Express!
Jupyter notebooks from the scikit-learn video series
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
NYU Deep Learning Spring 2020
Multi-user server for Jupyter notebooks
Jupyter notebook and datasets from the pandas video series
Jupyter notebooks for teaching/learning Python 3
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release 3 months ago