Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.

Recursive Neural Network for Text Generation.

A repository demonstrating different examples of LSTM.

RNNs with layer normalization; Prep package for tensorflow/addons, see v0.8.2, and commit https://github.com/tensorflow/addons/commit/cdb43ffd7e4b89d6ce8cdadcd62fec46c7f0f7fa

Estimating the growth or depreciation on exchange rates by using sentiment analysis method from social media comments

Here sentiments of the tweets posted by users in Twitter during COVID-19 pandemic situation are analyzed, whether a tweet belongs to the positive sentiment or negative sentiment. Here two recurrent neural network models (RNN) are used to predict the sentiment of a tweet which are simpleRNN and LSTM.

RNN

Estimating energy consumption in Megawatts (MW)

I previously illustrated two forecasting implementations with the same data set. This is the last one in these series using deep learning model.

A ML based elective recommendation webapp

This project involves building a sentiment analysis model using Recurrent Neural Networks (RNN) to classify movie reviews from the IMDb dataset as either positive or negative. The IMDb dataset consists of 50,000 highly polarized movie reviews, with 25,000 labeled as positive and 25,000 as negatives.

Sinewave forcasting using simpleRNN and LSTM model