479 Open source projects that are alternatives of or similar to ACT

Deep learning codes and projects using Python

Python library for Reservoir Computing using Echo State Networks

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

Char-RNN implemented using 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).

Computer-generated poetry

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.

Neural networks library for machine learning on PHP

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.

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

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

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).

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

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

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

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

The Official Deep Learning Framework for Route-based Place Recognition

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

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

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

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

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

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

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)

RMDL: Random Multimodel Deep Learning for Classification

Probabilistic Dialogue Act Classification for the Switchboard Corpus using an LSTM model

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.

PyTorch tutorial for learners

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

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

机器学习、深度学习、NLP实战项目

A tensorflow implementation of "Generating Sentences from a Continuous Space"

[PAMI 2021] Gating Revisited: Deep Multi-layer RNNs That Can Be Trained

An experimental web text editor that runs a LSTM model while you write to suggest new lines

Code for Stanford CS224D: deep learning for natural language understanding

Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)

Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.

TensorFlow Implementation of TCN (Temporal Convolutional Networks)

Sentiment Analysis LSTM recurrent neural network's.

State of the Art Neural Networks for Deep Learning

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

Online Handwriting Signature Verification using CNN + RNN.

keras project that parses and analyze english resumes

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

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.

📓 Notes for Andrew Ng's courses on deep learning

HDLTex: Hierarchical Deep Learning for Text Classification

Anomaly detection for temporal data using LSTMs

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 …

Spying using Smartwatch and Deep Learning

Generalised and highly customisable, hybrid-parallelism, database based, deep learning framework.

NLP tutorial

TensorFlow Implementation of Twitter Chatbot

Automatic trading bot (WIP)

News summarization using sequence to sequence model with attention in TensorFlow.

Singing Voice Separation via Recurrent Inference and Skip-Filtering Connections - PyTorch Implementation. Demo:

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