7013 Open source projects that are alternatives of or similar to Tensorflow Lstm Regression

Anomaly detection for temporal data using LSTMs

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

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

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.

Visualization Toolbox for Long Short Term Memory networks (LSTMs)

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

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

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

A Keras library for multi-step time-series 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.

Application of machine learning to the Coinbase (GDAX) orderbook

Neural machine translator for English2German translation.

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

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

PyTorch tutorial for learners

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

Training Diary

中文聊天机器人，基于10万组对白训练而成，采用注意力机制，对一般问题都会生成一个有意义的答复。已上传模型，可直接运行，跑不起来直播吃键盘。

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)

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

A neural network that transforms a design mock-up into a static website.

Using LSTM network for time series forecasting

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

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

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

Analysis and datasets about football (soccer)

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

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

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).

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

💫 Jupyter notebooks for spaCy examples and tutorials

文本情感分析

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

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

📃 **Unofficial** PyTorch Implementation of DA-RNN (arXiv:1704.02971)

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

🥕 Evolutionary Neural Networks in JavaScript

C# kernel for Jupyter

Notebooks and libraries for spatial/geo Python explorations

Machine learning models for time series analysis

The Go kernel for Jupyter notebooks and nteract.

The hands-on NLTK tutorial for NLP in Python

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.

PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.

Debugging, monitoring and visualization for Python Machine Learning and Data Science

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

A guide on how to set up Jupyter with Pyspark painlessly on AWS EC2 clusters, with S3 I/O support

Cryptocurrency Price Prediction Using LSTM neural network

Image Captioning using InceptionV3 and beam search

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

Jupyter's kernel for Elixir programming language

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

Teaching and Learning with Jupyter

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

Edit your Jupyter notebooks in Vim/Neovim

《程序员面试金典》(cc150)

F# for Jupyter Notebooks

Jupyter for Visual Studio Code

Anomaly detection implemented in Keras