777 Open source projects that are alternatives of or similar to Stock Trading Ml

Anomaly detection for temporal data using LSTMs

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

GANs for time series generation in pytorch

Using LSTM network for time series forecasting

Implementation of RNN for Time Series prediction from the paper https://arxiv.org/abs/1704.02971

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

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

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Library of autoencoders for sequential data

ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

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.

Annotation of ECG signals using deep learning, tensorflow’ Keras

Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)

Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs

an tutorial implement of voice conversion using pytorch

Sentence paraphrase generation at the sentence level

Process live and historical data from luftdaten.info, IRCELINE and OpenAQ. Filter by station-id, sensor-id and sensor-type, apply reverse geocoding, store into timeseries and RDBMS databases, publish to MQTT, output as JSON or visualize in Grafana.

Calculates various features from time series data. Python implementation of the R package tsfeatures.

Python implementation of soft-DTW.

Scientific time series and deep learning state of the art

stock predict by cnn and lstm

Merlion: A Machine Learning Framework for Time Series Intelligence

🎭 Sentiment Analysis of Twitter data using combined CNN and LSTM Neural Network models

Thio - a playground for real-time anomaly detection

OCR engine for all the languages

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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.

Visualize large time-series data in plotly

CRNN with attention to do OCR,add Chinese recognition

Cryptocurrency Price Prediction Using LSTM neural network

An interactive 3D animation using WebGL to depict a 2D predator prey ecology on a grid real-time mapped onto the surface of a 3D torus. Sound file is parsed then visualized both in time and frequency domains as well as rendered using Web Audio API - this is an exercise where I taught myself how to display data for an ongoing project on sound syn…

music generation with a classifying variational autoencoder (VAE) and LSTM

State of the art Chinese Word Segmentation with Bi-LSTMs

A collection of UNet and hybrid architectures in PyTorch for 2D and 3D Biomedical Image segmentation

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

Various methods for generating synthetic data for data science and ML

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

(Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"

PyTorch implementation of a 2D-LSTM Seq2Seq Model for NMT.

中文古诗自动作诗机器人，屌炸天，基于tensorflow1.10 api，正在积极维护升级中，快star，保持更新！

Chart.js plugin for live streaming data

An open-source, low-code machine learning library in Python

An open source SQL database designed to process time series data, faster

Hybrid Code Networks https://arxiv.org/abs/1702.03274

A pytorch implemention of "StyleNet: Generating Attractive Visual Captions with Styles"

Tidy anomaly detection

Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.

Video lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf

💡 A Distributed and High-Performance Monitoring System. Prometheus enterprise edition

Timelines Chart

Machine Learning Projects

High-performance time series algorithms for Ruby

🥕 Evolutionary Neural Networks in JavaScript

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