long-short-term-memory
There are 191 repositories under long-short-term-memory topic.
Rajat-dhyani/Stock-Price-Predictor
This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
gionanide/Speech_Signal_Processing_and_Classification
Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].
taufeeque9/HumanFallDetection
Real-time, Multi-person & Multi-camera Fall Detector in Python
tiberiu44/TTS-Cube
End-2-end speech synthesis with recurrent neural networks
LahiruJayasinghe/RUL-Net
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
FaustoNisida/Chatbot-Long-Short-Term-Memory
GPT-3 Chatbot with Long and Short Term Memory and advanced logic built in javascript with openai API - short and long memory, KYC, embeddings, openai, database, flexible, gpt-3.5-turbo, react
adobe/stringlifier
Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.
zhuofupan/Tensorflow-Deep-Neural-Networks
用Tensorflow实现的深度神经网络。
Zeeshanahmad4/chatgpt-knowledge-base-chatbot
An advanced chatbot that utilizes your own data to provide intelligent ChatGPT-style conversations using gpt-3.5-turbo and Ada for advanced embedding, as well as custom indexes and knowledgebase for a seamless user experience.
YangWangsky/tf_EEGLearn
A tensorflow implementation for EEGLearn
yxtay/char-rnn-text-generation
Character Embeddings Recurrent Neural Network Text Generation Models
guangyizhangbci/EEG_Riemannian
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
Sk70249/Wind-Energy-Analysis-and-Forecast-using-Deep-Learning-LSTM
A Deep Learning model that predict forecast the power generated by wind turbine in a Wind Energy Power Plant using LSTM (Long Short Term Memory) i.e modified recurrent neural network.
sankalpjain99/Automatic-Essay-Scoring
Created a web app that can automatically score essays. The grading model was trained using HP Essays Dataset from Kaggle. Used Long Short Term Memory (LSTM) network and machine learning algorithms to train model. WebApp was created using Flask framework.
mithi/deep-blueberry
If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!
skanderhamdi/attention_cnn_lstm_covid_mel_spectrogram
Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
safrooze/LSTNet-Gluon
Time-series prediction with LSTNet in Apache MXNet Gluon
khooinguyeen/Sign-Language-Translation
Sign language translation model for the app Look & Tell https://github.com/khooinguyeen/LookandTell-OfficialApp
theerfan/Maqenta
Generating music using quantum machine learning models. (QuGAN and QLSTM)
AFAgarap/ecommerce-reviews-analysis
Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)
albertusk95/intention-to-code-lstm
Source Code Generation Based On User Intention Using LSTM Networks
aosama16/Udacity-Deep-Learning-Nanodegree
My Projects Submission to Udacity's Deep Learning Nanodegree Program
ikmb/amino_acid_encoding_deep_learning_applications
The repository contains all the code for the paper amino acid encoding using deep learning application
Abhradipta/Fake-News-Detection
Fake News Detection Using Recurrent Neural Networks (RNNs) & Long Short Term Memory (LSTM).
MohamedSebaie/Coursera--Deep_Learning_Specialization--By_Anderw_Ng
Coursera (Deep_Learning_Specialization) By Andrew Ng and offered by deeplearning.ai.**Each of the below Courses Contains Notes, programming assignments, and quizzes.1- Neural Networks and Deep Learning;2- Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization; 3- Structuring Machine Learning Projects; 4- Convolutional Neural Networks;5- Sequence Models.
vinayakumarr/CNN-RNN
Image classification using CNN
thenomaniqbal/Traffic-flow-prediction
Long Short-Term Memory(LSTM) is a particular type of Recurrent Neural Network(RNN) that can retain important information over time using memory cells. This project includes understanding and implementing LSTM for traffic flow prediction along with the introduction of traffic flow prediction, Literature review, methodology, etc.
catcd/LSTM-CNN-SUD
Hybrid biLSTM and CNN architecture for Sentence Unit Detection
catcd/MASS
Large-scale Exploration of Neural Relation Classification Architectures
georgezoto/RNN-LSTM-NLP-Sequence-Models
Sequence Models repository for all projects and programming assignments of Course 5 of 5 of the Deep Learning Specialization offered on Coursera and taught by Andrew Ng, covering topics such as Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long Short Term Memory (LSTM), Natural Language Processing, Word Embeddings and Attention Model.
oem/bitcoin-prediction
A simple LSTM network to predict bitcoin closing prices
saadarshad102/Sentiment-Analysis-RNN-LSTM
Sentiment Analysis using Recurrent Neural Networks (RNN-LSTM) and Google News Word2Vec
sdw95927/Tang_Poetry_generator_by_LSTM
Train a Long-Short Term Memory neural network to write the Poetry of Tang Dynasty
ifrunistuttgart/RL_Integrated-Updraft-Exploitation
This repository includes a reinforcement learning framework for end-to-end type integrated thermal updraft localization and exploitation.
alexandrandom/BTC-LSTM-PRICE-PREDICTION-NLP
Bitcoin Price Prediction model - LSTM | Multivariable (Price&Polarity) Time Series Forecasting with NLP for Twitter Sentiments aka my Master's Thesis
CYBERDEVILZ/Stock-Market-Prediction
An attempt to predict the Stock Market Price using Long Short Term memory and plot its chart. By tweaking different hyper parameters, we get different trained models. The aim of this project is to identify the relation hidden in these hyper parameters.