This is a repo that compares the vanilla, stacked, CNN, encoder-decoder, bidirectional LSTMs

Implementation of an Attention-based LSTM Encoder-Decoder Approach for Abstractive Text Summarization

Stock market prediction of a stock using stacked LSTM

Forecasting and Prediction of Apple stock by creating a stacked LSTM model on previous data and trying to predict new stock price.

Stock values are very valuable but extremely hard to predict correctly for any human being on their own. This project seeks to solve the problem of Stock Prices Prediction by utilizes Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict future stock values

This GitHub repository contains the code for performing sentiment analysis on movie reviews. The dataset used for training and evaluation is sourced from Kaggle, ensuring a diverse and comprehensive collection of movie reviews.

generate formal speeches using language modeling

Predicting house prices using Ridge, SVR, GBR, XGBoost, LightGBM, Random Forest and Stacked CV

This repository contains an implementation of Stock Market prediction using Stacked LSTMs.

This repository is created to store different trained model and their results of executions in a structured manner according to their timeline and value.

Made the stock prices to be predicted from a 5 years dataset from TIINGO of APPLE company and worked on the next 30-day prediction. The final output made after applying 3 stacked layers of LSTM and a dense layer gave me a model with a rmse value of 284.

This repository contains `JPX Tokyo Stock Exchange Prediction`.

Text Sentiment Classification (Computational Intelligence Lab, ETH Zurich, 2018)

LSTM , CNN

stacked lstm model is trained on more than 7k hindi songs sequences to generate meaningful lyrics upto 20 words.

Academic project for CSE4022 - Natural Language Processing

Microsoft Stock Price (closing) Prediction using Stacked LSTM and ARIMA (6,1,6) models