644 Open source projects that are alternatives of or similar to Stockprediction

Automatic trading bot (WIP)

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

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

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

TensorFlow implementation of multi-layer recurrent neural networks for training and sampling from texts

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

A Python package for gender classification.

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

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

Anomaly detection for temporal data using LSTMs

Keras implementation of Legendre Memory Units

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)

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

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

Using LSTM network for time series forecasting

List of papers, code and experiments using deep learning for time series forecasting

Named Entity Recognition with RNN, implemented by Chainer

Image Captioning: Implementing the Neural Image Caption Generator with python

A Natural Language Toolkit for Indian Languages

PyTorch tutorial for learners

Use unsupervised and supervised learning to predict stocks

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

Neural machine translator for English2German translation.

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

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

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

News summarization using sequence to sequence model with attention in TensorFlow.

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Anomaly detection implemented in Keras

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

Lightweight C++11 library for building deep recurrent neural networks

A Keras library for multi-step time-series forecasting.

🥕 Evolutionary Neural Networks in JavaScript

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

Named Entity Recognition using multilayered bidirectional LSTM

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

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

The Official Deep Learning Framework for Route-based Place Recognition

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

Application of machine learning to the Coinbase (GDAX) orderbook

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

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

keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS

The deeplearning algorithms implemented by tensorflow

Models for predicting emotions from English tweets.

Weka package for the Deeplearning4j java library

datagrand 2019 information extraction competition rank9

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

Annotation of ECG signals using deep learning, tensorflow’ Keras