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

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

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

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.

Univariate Time Series Forecasting by LSTM

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

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

Stock market prediction of a stock using stacked LSTM

This repository contains `JPX Tokyo Stock Exchange Prediction`.

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

Academic project for CSE4022 - Natural Language Processing

Google_Stock_Price_Prediction-And-Forecasting-Using-Stacked-LSTM

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

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

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

Identifying offensive content in image and text

Sentiment Classifier using a bidirectional stacked RNN with LSTM/GRU cells for the Twitter sentiment analysis dataset