Lyrics-Generation-using-RNNs

Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.

Cuda implementation of Extended Long Short Term Memory (xLSTM) with C++ and PyTorch ports

This project provides implementations with Keras/Tensorflow of some deep learning algorithms for Multivariate Time Series Forecasting: Transformers, Recurrent neural networks (LSTM and GRU), Convolutional neural networks, Multi-layer perceptron

Time Series Analysis of Air Pollutants(PM2.5) using LSTM model

This repository contains the notebooks used in my project "Air quality analysis and forecasting"

Weather forecasting using recurrent neural network

In this project we will be building a model capable of generating notes and chords after learning from the dataset of songs we provide to our recurrent neural network and create songs. Before we start, let us recall few of the basic concepts and terminologies we will be using in this project and add to that knowledge the concepts required to successfully train our model to be an excellent composer.

This project contains the file of my undergraduate Final Year Project. This project aims to expose cyberbullying in Twitter by using Machine Learning to classify whether the tweet is suspicious or not. A deployment has been created using streamlit.

Time series analysis on NIFTY-50 index stock data. The project visualises trends in stock data and explores various time-series analysis models such as ARIMA, ARMA and deep learning models such as LTSM and RNN to predict stock prices with the highest accuracy.