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

Character Embeddings Recurrent Neural Network Text Generation Models

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.

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.

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!

Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound

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.

Sign language translation model for the app Look & Tell https://github.com/khooinguyeen/LookandTell-OfficialApp

Time-series prediction with LSTNet in Apache MXNet Gluon