Time Series Forecasting with Neural Networks
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Updated
Jan 9, 2022 - Python
Time Series Forecasting with Neural Networks
Recurrent Neural Networks (RNN's) for sentiment analysis on IMDB dataset from keras....
LSTM neural network to identify textual entailment
Deep Learning class projects from Kagle. All projects are individual projects conducted by me using pyhton (keras, tensor-flow, matplotlib and other libraries). Different Deep Neural Network (DNN) methods were used and results were compared based one efficiency and accuracy. Results and conclusions based on results were reported.
Simulation of "Triggering Proactive Business Process Adaptations via Online Reinforcement Learning" paper with proper steps and recreating the results
Hybrid Question Answering System project, based on SQuAD Dataset.
LSTM based Model for Real-time Stock Market Prediction on Unexpected Incidents
Solve simple contest problems with ML
This is a code repository for my semester project for CSCI 8980 Perception & Learning in Field Robotics, taught by Dr. Junaed Sattar in the Fall of 2021, at the University of Minnesota, Minneapolis, MN, USA.
API with Stock Prices Predictions 1d for helping on Swing Trade
Rnn (vanial, GRU and LSTM) from scratch
Hybrid Question Answering System project, based on SQuAD Dataset
Learning parities with various neural network architectures
⚡ STOCK MARKET PREDICTION is a Deep Learning based web application using LSTM model and that is used to predict the future stock prices based on 10 years historical data
🎬 Using an LSTM to generate movie titles
A character-based LSTM trained to generate words from a given list.
Pytorch based Neural Network Language Modeling (NNLM) Toolkit for easier and faster NNLM research and development. Result of my Master's Thesis work.
This project uses a recurrent neural network (RNN) with Long Short-Term Memory (LSTM) layers to generate text based on Shakespeare's works. The model is trained on a subset of Shakespeare's text and can generate new text sequences based on the learned patterns.
Framework for learning effective reduced order dynamics of molecular systems.
Neural Networks project for Intelligent Systems course at Tecnico, Lisbon.
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