6408 Open source projects that are alternatives of or similar to Rnn Notebooks

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

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

Keras tutorial for beginners (using TF backend)

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

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

Application of machine learning to the Coinbase (GDAX) orderbook

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

A cute multi-layer LSTM that can perform like a human 🎶

Word Embedding + LSTM + FC

Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

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.

All my experiments with AI and ML

Stock Price Prediction using Machine Learning Techniques

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

Sentiment Analysis with LSTMs in Tensorflow

Haste: a fast, simple, and open RNN library

RNN and general weights, gradients, & activations visualization in Keras & TensorFlow

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。

Chinese Poetry Generation

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

My Attempt(s) In The World Of ML/DL....

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.

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

Recurrent Additive Networks for Tensorflow

Recurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano

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

Natural Language Processing with TensorFlow, published by Packt

Predict Cryptocurrency Price with Deep Learning

PyTorch tutorial for learners

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

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.

A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.

Deep Learning

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

All about Neural Networks!

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow

Cryptocurrency Price Prediction Using LSTM neural network

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.

🔬 Nano size Theano LSTM module

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

Repository for the tutorial on Sequence-Aware Recommender Systems held at TheWebConf 2019 and ACM RecSys 2018

[RSE21] Pytorch code for hierarchical time series classification with multi-stage convolutional RNN

Image Captioning using InceptionV3 and beam search

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！

BasicOCR是一个致力于解决自然场景文字识别算法研究的项目。该项目由长城数字大数据应用技术研究院佟派AI团队发起和维护。

Multiple implementations for abstractive text summurization , using google colab

[2017知乎看山杯 多标签 文本分类] ye组(第六名) 解题方案

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

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

百度云魅族深度学习应用大赛

文本情感分析

Neural Turing Machines (NTM) - PyTorch Implementation

Automatically generate headlines to short articles

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

Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes

Sequence prediction using recurrent neural networks(LSTM) with TensorFlow

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