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.
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
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…
Real-time, Multi-person & Multi-camera Fall Detector in Python
用Tensorflow实现的深度神经网络。
End-2-end speech synthesis with recurrent neural networks
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
A tensorflow implementation for EEGLearn
Character Embeddings Recurrent Neural Network Text Generation Models
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.
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.
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.
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.
Time-series prediction with LSTNet in Apache MXNet Gluon
Statistical Analysis on E-Commerce Reviews, with Sentiment Classification using Bidirectional Recurrent Neural Network (RNN)
My Projects Submission to Udacity's Deep Learning Nanodegree Program
Sentiment Analysis using Recurrent Neural Networks (RNN-LSTM) and Google News Word2Vec
Accepted in IEEE Transactions on Emerging Topics in Computational Intelligence
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- Convolut…
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