Topic: long-short-term-memory Goto Github
Some thing interesting about long-short-term-memory
Some thing interesting about long-short-term-memory
long-short-term-memory,It analyses the movie review entered by a user for any specific movie and analyses what is the sentiment of the review. It helps the companies rate the movie and understand crowd sentiment regarding it. Sentiment analysis is a natural language processing problem where text is understood and the underlying intent is predicted.
User: aadimangla
long-short-term-memory,Fake News Detection Using Recurrent Neural Networks (RNNs) & Long Short Term Memory (LSTM).
User: abhradipta
long-short-term-memory,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.
Organization: adobe
long-short-term-memory,Hippocampus spike activity related to the depression-related behaviors after stress. Propose the stress determinator
User: adriandliu
long-short-term-memory,Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)
User: afagarap
Home Page: https://arxiv.org/abs/1805.03687
long-short-term-memory,Source Code Generation Based On User Intention Using LSTM Networks
User: albertusk95
long-short-term-memory,Bitcoin Price Prediction model - LSTM | Multivariable (Price&Polarity) Time Series Forecasting with NLP for Twitter Sentiments aka my Master's Thesis
User: alexandrandom
long-short-term-memory,My Projects Submission to Udacity's Deep Learning Nanodegree Program
User: aosama16
long-short-term-memory,Hybrid biLSTM and CNN architecture for Sentence Unit Detection
User: catcd
long-short-term-memory,Large-scale Exploration of Neural Relation Classification Architectures
User: catcd
Home Page: http://www.aclweb.org/anthology/D18-1250
long-short-term-memory,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.
User: cyberdevilz
long-short-term-memory,Using Long Short-term Memory recurrent neural networks to generate highly realistic cursive handwriting in a wide variety of styles.
Organization: data-science-community-srm
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
User: faustonisida
long-short-term-memory,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.
User: georgezoto
long-short-term-memory,Opinion recommendation is a task, recently introduced, for consistently generating a text review and a rating score that a certain user would give to a certain product, which has never seen before. Input information driving recommendation is text reviews and ratings for this product contributed by other users and text reviews submitted by the user under consideration for other products. The aforementioned task faces the same problems emerging in text generation using neural networks, namely repetition and specificity. In this paper, it is experi- mentally demonstrated that by employing coverage loss during training, repetition is reduced without adding extra parameters. Furthermore, the amount of repetition in the generated text review is defined as a measure of the captured information. Such measure is used to improve rating score prediction significantly during testing.
User: gionanide
long-short-term-memory,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].
User: gionanide
long-short-term-memory,Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
User: guangyizhangbci
long-short-term-memory,This repository includes a reinforcement learning framework for end-to-end type integrated thermal updraft localization and exploitation.
Organization: ifrunistuttgart
long-short-term-memory,The repository contains all the code for the paper amino acid encoding using deep learning application
Organization: ikmb
long-short-term-memory,Deep sequence models for protein classification
User: jgbrasier
long-short-term-memory,This project compares the accuracy of different machine learning models in the identification and classification of bearing faults from time-series vibration data.
User: kaushikpalani
long-short-term-memory,Sign language translation model for the app Look & Tell https://github.com/khooinguyeen/LookandTell-OfficialApp
User: khooinguyeen
Home Page: https://github.com/khooinguyeen/LookandTell-OfficialApp
long-short-term-memory,Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
User: lahirujayasinghe
long-short-term-memory,Named Entity Recognition - Python - Keras
User: lbasek
long-short-term-memory,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!
User: mithi
Home Page: https://mithi.github.io/deep-blueberry/
long-short-term-memory,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.
User: mohamedsebaie
long-short-term-memory,A simple LSTM network to predict bitcoin closing prices
User: oem
long-short-term-memory,LSTM Network from Scratch in C++
User: pskrunner14
long-short-term-memory,Demand prediction for Uber based on Multivariate Time Series Forecasting with LSTM (long short-term memory)
User: rabieifk
long-short-term-memory,This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
User: rajat-dhyani
long-short-term-memory,This is a practical implementation implementing neural networks on top of fasttext as well as word2vec word embeddings.
User: rounayak
long-short-term-memory,Sentiment Analysis using Recurrent Neural Networks (RNN-LSTM) and Google News Word2Vec
User: saadarshad102
long-short-term-memory,Time-series prediction with LSTNet in Apache MXNet Gluon
User: safrooze
long-short-term-memory,In this notebook, I implemented a recurrent neural network (Long short-term memory) using PyTorch that performs sentiment analysis.
User: salehsargolzaee
long-short-term-memory,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.
User: sankalpjain99
long-short-term-memory,Train a Long-Short Term Memory neural network to write the Poetry of Tang Dynasty
User: sdw95927
long-short-term-memory,Based on a Hybrid CNN-LSTM Network, an automated predicitve algorithm is constructed.
User: shahriar-rahman
long-short-term-memory,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.
User: sk70249
Home Page: https://sk70249.github.io/Wind-Energy-Analysis-and-Forecast-using-Deep-Learning-LSTM/
long-short-term-memory,Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
User: skanderhamdi
long-short-term-memory,Real-time, Multi-person & Multi-camera Fall Detector in Python
User: taufeeque9
long-short-term-memory,Generating music using quantum machine learning models. (QuGAN and QLSTM)
User: theerfan
long-short-term-memory,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.
User: thenomaniqbal
long-short-term-memory,End-2-end speech synthesis with recurrent neural networks
User: tiberiu44
Home Page: https://tiberiu44.github.io/TTS-Cube/
long-short-term-memory,LSTM Sentiment Analysis
User: victor-iyi
long-short-term-memory,Image classification using CNN
User: vinayakumarr
long-short-term-memory,A tensorflow implementation for EEGLearn
User: yangwangsky
long-short-term-memory,Character Embeddings Recurrent Neural Network Text Generation Models
User: yxtay
long-short-term-memory,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.
User: zeeshanahmad4
long-short-term-memory,用Tensorflow实现的深度神经网络。
User: zhuofupan
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