Build an algorithm that can predict multiple future states of Limit Order Books using high-frequency, multi-variate, short time-frame data

Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.

The objective of this data science project is to conduct sentiment analysis on tweets related to the FIFA World Cup 2022. By analyzing the sentiment of tweets, the project aims to gain insights into the public's perception, emotions, and opinions surrounding the event.

In this work, I trained a Long Short Term Memory (LSTM) network to detect fake news from a given news corpus. This project could be practically used by media companies to automatically predict whether the circulating news is fake or not. The process could be done automatically without having humans manually review thousands of news-related artic…

XSS Attack Machine Learning detection

This repository include basic time series analysis with different python library.

A repository to make basic predictions on a pharmaceutical data set, using machine learning and deep learning concepts. This is a week III project of 10 academy batch VI intensive training.

A forecasting system for multiple sectors that uses ARIMA, ETS, SVR, and other models displayed on a user friendly interface with different viewing options.

Image caption generator is a process of recognizing the context of an image and annotating it with relevant captions using deep learning, and computer vision. we will build an image caption generator to load a random image and give some captions describing the image. We will use Convolutional Neural Network (CNN) for image feature extraction and…

LTSM Neural network to predict the top comment of any given reddit post

Applies Machine Learning approach to predict spam.