5921 Open source projects that are alternatives of or similar to Commitgen

USC urban data science course series with Python and Jupyter

Code for our paper "Generalized Orderless Pooling Performs Implicit Salient Matching" published at ICCV 2017.

🔤 Calculate average word embeddings (word2vec) from documents for transfer learning

자연어 처리와 관련한 여러 튜토리얼 저장소

A 2-unit decal run by [email protected]'s education team

Machine Learning University: Accelerated Computer Vision Class

Multilayer Neural Network using numpy.

python notebooks accompanying the book Make Your Own GAN

Build a neural network to code a basic a HTML and CSS website based on a picture of a design mockup.

A Conversion tool to convert YOLO v3 Darknet weights to TF Lite model (YOLO v3 PyTorch > ONNX > TensorFlow > TF Lite), and to TensorRT (YOLO v3 Pytorch > ONNX > TensorRT).

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

Web scraping to get articles for a given query. It returns an spreadsheet with titles, abstracts, doi and references of the article

Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC

Short Course - Applied Machine Learning for Security Informatics

Tensorflow实战学习笔记、代码、机器学习进阶系列

LSTM-CRF for NER with ConLL-2002 dataset

A workshop on data privacy methods for data scientists.

Blackbox attacks for deep neural network models

Diseases Detection from NIH Chest X-ray data

DSSG Workshops

searching large heterogenous data dumps with Universal Sentence Encoder

Machine Learning in Asset Management (by @firmai)

『파이썬과 리액트를 활용한 주식 자동 시스템』 예제 코드

A Python package to effortlessly assemble images in comparison figures. Supports LaTeX, PPTX, and HTML.

Code Repository for the online course Feature Selection for Machine Learning

I will update this repository to learn Machine learning with python with statistics content and materials

[ICML 2020] PyTorch Code for "Efficient Continuous Pareto Exploration in Multi-Task Learning"

TensorFlow Tutorial for Time Series Prediction

Mask On-Off control with computer vision

Some notebooks

Twitter sentiment analysis based on Apache Spark, MLlib, Scala and Akka.

Multilingual word vectors in 78 languages

This repo contains code related to german traffic sign detection and classification using Faster-RCNN

Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥

Code from my blog post & online course

Python tutorials as Jupyter Notebooks for NLP, ML, AI

Mask R-CNN

This a Deep learning AI system which recognize handwritten characters, Here I use chars74k data-set for training the model

PyTorch DataSet and Jupyter demos for MusicNet

Deep reinforcement learning. In scikit-learn. In less than 50 effective lines.

《深度卷积网络：原理与实践》现已在淘宝天猫京东当当发售. 这里是其中的代码下载.

Implementation of "FastSpeech: Fast, Robust and Controllable Text to Speech"

Phi_K correlation analyzer library

Attention, I'm Trying to Speak: End-to-end speech synthesis (CS224n '18)

Training Toolbox for Caffe

Open source project to deploy Keras Deep Learning models packaged as Docker containers on Kubernetes.

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Computer Vision Nanodegree program from Udacity

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

This Repo Contains all the exercise files for Data Science Course of 365 Datascience . The repo is split into the relevant folders & there is one exercise folder which contains all the files of that course. Don't forget to star it :D

What Twitter reveals about the differences between cities and the monoculture of the Bay Area

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

A Los Angeles Times analysis of arrests of the homeless by the LAPD

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

Train a BERT model with TensorFlow 2.0 to automatically tag StackOverflow questions!