This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
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Updated
Sep 28, 2020 - HTML
This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
Real-time, Multi-person & Multi-camera Fall Detector in Python
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…
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
End-2-end speech synthesis with recurrent neural networks
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.
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
用Tensorflow实现的深度神经网络。
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.
A tensorflow implementation for EEGLearn
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.
Character Embeddings Recurrent Neural Network Text Generation Models
IEEE Transactions on Emerging Topics in Computational Intelligence
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.
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.
Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
Generating music using quantum machine learning models. (QuGAN and QLSTM)
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!
Sign language translation model for the app Look & Tell https://github.com/khooinguyeen/LookandTell-OfficialApp
Time-series prediction with LSTNet in Apache MXNet Gluon
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