932 Open source projects that are alternatives of or similar to Sequitur

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.

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

Anomaly detection for temporal data using LSTMs

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

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

DanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)

Hands-on in-person workshop for Deep Learning with TensorFlow

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

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

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

A stock trading bot that uses machine learning to make price predictions.

Using LSTM network for time series 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.

Annotation of ECG signals using deep learning, tensorflow’ Keras

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.

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

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

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

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

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

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

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

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

Use unsupervised and supervised learning to predict stocks

LSTM Mobility Model implementation using Tensorflow

Anomaly detection for streaming data using autoencoders

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.

GANs for time series generation in pytorch

Deep learning meets molecular dynamics.

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

Time series analysis in Java

Variational Autoencoder for Dimensionality Reduction of Time-Series

A simple Tensorflow based library for deep and/or denoising AutoEncoder.

Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html

Visualization techniques for the latent space of a convolutional autoencoder in Keras

Implementation of time series compression method from the Facebook's Gorilla paper

Hurst exponent evaluation and R/S-analysis in Python

A Bitcoin trade robot based on Tensorflow LSTM model.Just for fun.

Anomaly detection tutorial on univariate time series with an auto-encoder

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

Neural network models for joint POS tagging and dependency parsing (CoNLL 2017-2018)

An open source library for Fuzzy Time Series in Python

PyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks

Time Series Cross-Validation -- an extension for scikit-learn

Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

Tutorial Sessions for SciPy Con 2019

Extending broom for time series forecasting

scikit-learn-inspired time series

TensorFlow template application for deep learning

semantic analysis using word2vector, doc2vector,lstm and other method. mainly for text similarity analysis.

基于RNN生成古诗

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Live Quant Trading Framework for Robinhood, using IEX Trading and AlphaVantage for Free Prices.

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

Load forcasting on Delhi area electric power load using ARIMA, RNN, LSTM and GRU models

Keras implementation of Legendre Memory Units

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

Generative Adversarial Networks and Autoencoders for 3D Shapes

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