The purpose of this project is to predict stock prices using historical data and financial indicators with LSTM networks. It involves data extraction, cleaning, model training, and an interactive app for predictions. This tool aids financial analysts, portfolio managers, and investors in making informed decisions.

This repository contains analysis and predictive modeling of household electricity consumption using Python. It includes data cleaning, exploratory data analysis (EDA), time series forecasting (ARIMA, SARIMA, LSTM), and model evaluation to optimize energy usage.

The repository contains all the code for the paper amino acid encoding using deep learning application

Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Recurrent Neural Network (RNN) regressor model that predicts energy demand in t-horizon, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ03

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.

This repository contains the code for training a LSTM network for translating from english to hindi language

A video call application that recognizes gestures (signal language) and converts them into text and sound.

Real-time, Multi-person & Multi-camera Fall Detector in Python

This repo contains all the necessary files to give you an idea of the complexity of an undergrad capstone project.

Stock Trend Prediction with LSTM is a powerful tool designed to empower users with insights into the dynamic world of stock market trends. Leveraging cutting-edge technologies such as Long Short-Term Memory (LSTM) networks and real-time data from Yahoo Finance, this project enables users to forecast future price movements of stocks with precision.

This repository features notebooks and datasets for predicting Tesla (TSLA) stock prices using LSTM models. Explore historical data, forecast trends, and gain insights into TSLA's market movements.

Fundamentals of Biometric Systems Design Assignments

Documentation related to RNN

Data Science Project: Comparing 3 Deep Learning Methods (CNN, LSTM, and Transfer Learning).

This repository contains the code on how to train an LSTM network from scratch to generate text.

Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.

This project implements an Artificial Music Generator using LSTM (Long Short-Term Memory) networks, a type of recurrent neural network (RNN). The system generates music character by character based on a given input dataset.

This is a repository of AI projects that i did during my master's degree in computer science.

Deep Learning in python

Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.