5921 Open source projects that are alternatives of or similar to Swift Models

A pedagogical implementation of Autograd

coursera吴恩达机器学习课程作业自写Python版本+Matlab原版

Efficient Image Captioning code in Torch, runs on GPU

The codes I made while I practiced various TensorFlow examples

fast.ai early development experiments

Data Analysis Baseline Library

A Chrome extension that adds a 3d photo effect to instagram pages.

My solution to the book <A collection of Data Science Take-home Challenges>

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

数据科学的笔记以及资料搜集

A TensorFlow implementation of DeepMind's Differential Neural Computers (DNC)

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.

Recipes for using Python's pandas library

Code, exercises and tutorials of my personal blog ! 📝

Proposes neural networks that can generate animation of virtual characters for different actions.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

PyTorch and Tensorflow functional model definitions

Time series classification and clustering code written in Python.

Environment for reinforcement-learning algorithmic trading models

Lectures for INFO8010 - Deep Learning, ULiège

a tensorflow implementation of WGAN

提供对YOLOv3及Tiny的多种剪枝版本，以适应不同的需求。

Korean BERT pre-trained cased (KoBERT)

An adversarial example library for constructing attacks, building defenses, and benchmarking both

PyBites Code Challenges

Early stopping for PyTorch

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)

My implementations of cs231n 2017

Preparing for machine learning interviews

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

this repository accompanies the book "Grokking Deep Learning"

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

PyTorch/TorchScript compiler for NVIDIA GPUs using TensorRT

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

Simple but useful Python web scraping tutorial code.

Deep Learning Cookbox

Training Very Deep Neural Networks Without Skip-Connections

An autonomous AI racecar using NVIDIA Jetson Nano

Bayesian Deep Learning Benchmarks

fast.ai Courses

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

Introduction to Deep Learning for Natural Language Processing

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

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

跟大咖一起读源码

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

Some work of Andrew Ng's course on Coursera

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/

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"

《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、深度学习研究人员和爱好者参考！

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Python implementation of KNN and DTW classification algorithm

Python Deep Dive Course - Accompanying Materials