6150 Open source projects that are alternatives of or similar to Deep Ml Meetups

A curated list of practical business machine learning (BML) and business data science (BDS) applications for Accounting, Customer, Employee, Legal, Management and Operations (by @firmai)

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications

GitHub Action for repo2docker

Compilation of R and Python programming codes on the Data Professor YouTube channel.

📚 [.md & .ipynb] Series of Artificial Intelligence & Deep Learning, including Mathematics Fundamentals, Python Practices, NLP Application, etc. 💫 人工智能与深度学习实战，数理统计篇 | 机器学习篇 | 深度学习篇 | 自然语言处理篇 | 工具实践 Scikit & Tensoflow & PyTorch 篇 | 行业应用 & 课程笔记

This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

Repo that contains the supporting material for O'Reilly Webinar "An Intro to Predictive Modeling for Customer Lifetime Value" on Feb 28, 2017

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog

The blog post about Kubeflow, including all materials

Data-Driven Exploration of the R Community

Learning numerical computing with notebooks for all ages.

Virgilio is developed and maintained by these awesome people. You can email us virgilio.datascience (at) gmail.com or join the Discord chat.

A day to day plan for this challenge. Covers both theoritical and practical aspects

Train multi-task image, text, or ensemble (image + text) models

Code, Notebooks and Examples from Practical Business Python

An OCaml kernel for Jupyter (IPython) notebook

Melusine is a high-level library for emails classification and feature extraction "dédiée aux courriels français".

A New, Interactive Approach to Learning Data Science

A repository to keep track of all the code that I end up writing for my blog posts.

【运筹OR帷幄|数据科学】pandas教程系列电子书

A community run, 5-day PyTorch Deep Learning Bootcamp

Putting machine learning in the hands of cancer biologists

CapsNet (from "Dynamic Routing Between Capsules") implemented in pytorch.

PRML algorithms implemented in Python

Tools for pen plotting in Python

Skin cancer detection project

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Materials for "Bayesian Methods for Machine Learning" Coursera MOOC

Board files to build Ultra 96 PYNQ image

Workshop to demonstrate how to apply NN based algorithms to stock market data and forecast price movements.

Python library for interactive topic model visualization. Port of the R LDAvis package.

攻城狮之家B站视频课程课件合集2，1号仓库https://github.com/JokerJohn/bilibili_notes.git

A Smooth Representation of SO(3) for Deep Rotation Learning with Uncertainty.

Topic modeling with word vectors

Learning Vis Tools: Tutorial materials for Data Visualization course at HKUST

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

Projecting images to latent space with StyleGAN2.

学习笔记代码

开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.

Reinforcement Learning research

Hadoop, Spark and Storm based anomaly detection implementations for data quality, cyber security, fraud detection etc.

Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"

All my experiments with AI and ML

Code for CS570, Essentials of Data Science

IPython Notebook for training a word-level Convolutional Neural Network model for sentiment classification task on Yelp-Challenge-2016 review dataset.

IJulia notebooks for AA228/CS238 Decision Making Under Uncertainty course at Stanford University

CS224D Assignments

Implementation of Excitation Backprop in Caffe

Periodic Spatial Generative Adversarial Networks

machine learning

Tous les codes utilisés dans la série YouTube Python Spécial Machine Learning !

Darwin Core

Reproducible Data Analysis Workflow in Jupyter

Bias detection in the news. Back and front end for areyoufakenews.com

Re-implementation of the m-RNN model using TensorFLow

Set of scripts and data for reproducing dog breed classification model training, analysis, and inference.

Machine learning with Python tutorial at MSU Data Science 2018