1113 Open source projects that are alternatives of or similar to Deep Time Series Prediction

The deeplearning algorithms implemented by tensorflow

Code for National Data Science Bowl. 10th place.

Keras implementation of Legendre Memory Units

Tensorflow Implementation of MAML

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

1st Place Solution for Zhihu Machine Learning Challenge . Implementation of various text-classification models.(知乎看山杯第一名解决方案)

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Google Summer of Code 2017 Project: Development of Speech Recognition Module for Red Hen Lab

Using Machine Learning to predict the type of exercise from movement data

Re-implementation of Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling (T. Shen et al., ICLR 2018) on Pytorch.

top 1% solution to toxic comment classification challenge on Kaggle.

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

This package contains an OCR engine - libtesseract and a command line program - tesseract. Tesseract 4 adds a new neural net (LSTM) based OCR engine which is focused on line recognition, but also still supports the legacy Tesseract OCR engine of Tesseract 3 which works by recognizing character patterns. Compatibility with Tesseract 3 is enabled by using the Legacy OCR Engine mode (--oem 0). It also needs traineddata files which support the legacy engine, for example those from the tessdata repository.

Solution to the Outbrain Click Prediction competition

A PyTorch Tutorials of Sentiment Analysis Classification (RNN, LSTM, Bi-LSTM, LSTM+Attention, CNN)

TensorFlow implementation of VQ-VAE with WaveNet decoder, based on https://arxiv.org/abs/1711.00937 and https://arxiv.org/abs/1901.08810

Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute

keras를 이용한 딥러닝 기초 학습

Speech commands recognition with PyTorch

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

PyTorch implementation of some attentions for Deep Learning Researchers.

Generating Text using Deep Learning in Python - LSTM, RNN, Keras

Activity Recognition from 2D pose using an LSTM RNN

Embedding, NMT, Text_Classification, Text_Generation, NER etc.

Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, and clause indexing

Some of the ML and DL related reading materials, research papers that I've read

A Julia machine learning framework

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

A collection of notebooks of my Machine Learning class written in python 3

Collection of stats, modeling, and data science tools in Python and R.

All about Neural Networks!

Artificial Neural Networks for Scala

An Interactive Approach to Understanding Deep Learning with Keras

Explore Action Recognition

implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)

A fast LSTM Language Model for large vocabulary language like Japanese and Chinese

使用Theano实现的一些RNN代码，包括最基本的RNN，LSTM，以及部分Attention模型，如论文MLSTM等

Open solution to the Data Science Bowl 2018

Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

DELTA is a deep learning based natural language and speech processing platform.

DeFactoNLP: An Automated Fact-checking System that uses Named Entity Recognition, TF-IDF vector comparison and Decomposable Attention models.

A bidirectional LSTM with attention for multiclass/multilabel text classification.

enhance seq2seq model for open ended dialog generation

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

Solution to Kaggle - Web Traffic Time Series Forecasting

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

记录我学习数据挖掘过程的笔记和见到的奇技，持续更新～

第三届魔镜杯 智能客服问题相似性算法设计 第12名解决方案

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

Delightful npm packages that make you say "wow, didn't know that was possible!"

iPython notebook and Android app that shows how to build LSTM model in TensorFlow and deploy it on Android

Oriented SSD for "Kaggle Airbus Ship Detection Challenge"

Python3 project applying Gaussian process regression for forecasting stock trends

TensorFlow template application for deep learning

基于卷积神经网络的语音识别声学模型的研究

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

Sample notebooks for Kaggle competitions

Regression range finder for Mozilla nightly builds

A Chainer implementation of VQ-VAE.