5967 Open source projects that are alternatives of or similar to Shapash

Notebooks and code for the book "Introduction to Machine Learning with Python"

Re-implementation of TensorFlow in pure python, with an emphasis on code understandability

My blogs and code for machine learning. http://cnblogs.com/pinard

Normalizing flows in PyTorch. Current intended use is education not production.

Early stopping for PyTorch

Image Captcha Solving Using TensorFlow and CNN Model. Accuracy 90%+

Code for "PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation" CVPR 2019 oral

All course materials for the Zero to Mastery Machine Learning and Data Science course.

A script that creates train, valid and test datasets for the ranking task from Ubuntu corpus dialogs.

Principal Component Analysis on music loops

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

PyBites Code Challenges

Repository containing notebooks of my posts on Medium

My implementations of cs231n 2017

Machine Learning toolbox for Humans

A CLI tool to convert CSV / Excel / HTML / JSON / Jupyter Notebook / LDJSON / LTSV / Markdown / SQLite / SSV / TSV / Google-Sheets to a SQLite database file.

The Open Architecture Playbook. Use it to create better and faster (IT)Architectures. OSS Tools, templates and more for solving IT problems using real open architecture tools that work!

Deep Learning Cookbox

Use evolutionary algorithms instead of gridsearch in scikit-learn

fast.ai Courses

以撸代码的形式学习Python

Introduction to Deep Learning for Natural Language Processing

Code samples for AI fundamentals

Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library

Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

Brushing and linking for big data

Korean BERT pre-trained cased (KoBERT)

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

Temporary home for fastai v2 while it's being developed

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Ten thousand books, six million ratings

Preparing for machine learning interviews

Code for "High-Precision Model-Agnostic Explanations" paper

this repository accompanies the book "Grokking Deep Learning"

From the basics to slightly more interesting applications of Tensorflow

PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT

Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

Simple but useful Python web scraping tutorial code.

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

Training Very Deep Neural Networks Without Skip-Connections

Exercise notebooks for CVND.

Bayesian Deep Learning Benchmarks

Keras documentation, hosted live at keras.io

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 series of machine learning tutorials for Torch7

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

Source code accompanying O'Reilly book: Machine Learning Design Patterns

ebook Machine Learning cơ bản

跟大咖一起读源码

Tutorial for Sentiment Analysis using Doc2Vec in gensim (or "getting 87% accuracy in sentiment analysis in under 100 lines of code")

Some work of Andrew Ng's course on Coursera

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

深度学习笔记

Models and examples built with Swift for TensorFlow

机器学习算法的公式推导以及numpy实现

A collection of miscellaneous thoughts that aren't on my blog.