787 Open source projects that are alternatives of or similar to Probabilistic-RNN-DA-Classifier

Computer-generated poetry

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

A variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.

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.

No description or website provided.

总结了一些可以用作聊天机器人训练实作的文字语聊，包含中英文不同语言

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<머신러닝 교과서 with 파이썬, 사이킷런, 텐서플로>의 코드 저장소

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

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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.

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

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Curated List of Persian Natural Language Processing and Information Retrieval Tools and Resources

All my experiments with AI and ML

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

Entirety.ai Intuition to Implementation Meetup Content.

This repo provides projects on deep-learning mainly using Tensorflow 2.0

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

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

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

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs

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

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

Chatbot in 200 lines of code using TensorLayer

おーぷん2ちゃんねるをクロールして作成した対話コーパス

Deep learning codes and projects using Python

PyTorch tutorial for learners

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)

Data augmentation for NLP, presented at EMNLP 2019

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

THEANO-KALDI-RNNs is a project implementing various Recurrent Neural Networks (RNNs) for RNN-HMM speech recognition. The Theano Code is coupled with the Kaldi decoder.

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

Tensorflow implementation of "Tracking the World State with Recurrent Entity Networks" [https://arxiv.org/abs/1612.03969] by Henaff, Weston, Szlam, Bordes, and LeCun.

collect the open dialog corpus and some useful data processing utils.

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).

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Neural networks library for machine learning on PHP

RMDL: Random Multimodel Deep Learning for Classification

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The Official Deep Learning Framework for Route-based Place Recognition

Char-RNN implemented using TensorFlow.

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

No description or website provided.

Alternative approach for Adaptive Computation Time in TensorFlow

📓 Notes for Andrew Ng's courses on deep learning

Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

Simple library to work with pre-trained ELMo models in TensorFlow

Uses RNN on the Nietzsche dataset

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Automatic trading bot (WIP)

🧠👨‍💻Deep Learning Specialization • Lecture Notes • Lab Assignments

RNN(LSTM, GRU) in Theano with mini-batch training; character-level language models in Theano

A Visual Dialogue Editor made using the Godot Engine

Node based dialogue system

Rich Context leaderboard competition, including the corpus and current SOTA for required tasks.