Open Machine Learning Course
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Updated
May 22, 2023 - Python
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.
Open Machine Learning Course
Plain python implementations of basic machine learning algorithms
学习闭环《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...)
Jupyter notebooks in the terminal
Jupyter notebooks in Russian. Introduction to Python, basic algorithms and data structures
Pynamical is a Python package for modeling and visualizing discrete nonlinear dynamical systems, chaos, and fractals.
A cli tool to convert and manage jupyter notebook blogs. Proudly host your notebooks even as a static site.
Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.
Image segmentation - general superpixel segmentation & center detection & region growing
GraphBLAS for Python
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
[tutorial]A functional, Data Science focused introduction to Python
Vim plugin for editing Jupyter ipynb files via jupytext
Presentation Materials for my "Sound Analysis with the Fourier Transform and Python" OSCON Talk.
Multi-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.
A strongly-typed genetic programming framework for Python
Code repository for a paper "Optic Disc and Cup Segmentation Methods for Glaucoma Detection with Modification of U-Net Convolutional Neural Network"
A Python library for structural analysis using the finite element method
Exploring the simple sentence similarity measurements using word embeddings
Created by Fernando Pérez, Brian Granger, and Min Ragan-Kelley
Released December 2011
Latest release Today