398 Open source projects that are alternatives of or similar to Semanaly

Plain Stock Close-Price Prediction via Graves LSTM RNNs

copper price(time series) prediction using bpnn and lstm

GANs for time series generation in pytorch

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

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

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

The deeplearning algorithms implemented by tensorflow

Use unsupervised and supervised learning to predict stocks

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond

Tensorflow Implementation of GAN modeling for sequential data

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

主流ocr算法研究实验性的项目，目前实现了CNN+BLSTM+CTC架构

Neural word segmentation with rich pretraining, code for ACL 2017 paper

Bitcoin price Prediction ( Time Series ) using LSTM Recurrent neural network

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

Time series based anomaly detector

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

Machine learning, in numpy

A Python package for gender classification.

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

AIOpen是一个按人工智能三要素（数据、算法、算力）进行AI开源项目分类的汇集项目，项目致力于跟踪目前人工智能（AI）的深度学习（DL）开源项目，并尽可能地罗列目前的开源项目，同时加入了一些曾经研究过的代码。通过这些开源项目，使初次接触AI的人们对人工智能（深度学习）有更清晰和更全面的了解。

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

convolutional lstm implementation in pytorch

Tensorflow-LSTM-CRF tool for Named Entity Recognizer

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

Augmenting word embeddings with their surrounding context using bidirectional RNN

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

Social LSTM using PyTorch for Vehicle Data

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

Sorting numbers with pointer networks

datagrand 2019 information extraction competition rank9

📚 Text classification library with Keras

PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot

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.

Keras implementation of video classifier

The Official Deep Learning Framework for Route-based Place Recognition

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Spectral-Spatial Unified Networks for Hyperspectral Image Classification

Sarcasm detection on tweets using neural network

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

Predict Race and Ethnicity Based on the Sequence of Characters in a Name

Efficient and easy to use transliteration for Indian languages

PyTorch tutorial for learners

Another attempt to use Deep-Learning in the financial markets

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

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

Multitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587

All about Neural Networks!

Implementation of "Generating Sequences With Recurrent Neural Networks" https://arxiv.org/abs/1308.0850

CNN, LSTM, NBOW, fasttext 中文文本分类

基于RNN生成古诗

A Collection of resources I have found useful on my journey finding my way through the world of Deep Learning.

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

A (CNN+)RNN(LSTM/BiLSTM)+CRF model for sequence labelling.😏

Tensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification

Implementation of the paper - Generative Recurrent Networks for De Novo Drug Design.