This project uses XGBoost to predict hourly energy consumption based on historical data, leveraging time-based features like hour, day of week, and month.

How to build a simple neural network from scratch using Numpy and linear algebra without relying on high-level libraries like TensorFlow or Keras.

This is a repository that addresses the challenges provided by "ML Code Challenges" website!

Appling unsupervised learning (Autoencoder) model to detect fraudulent transactions.

Here, I developed a neural network that’s all about spotting faces, whether in images or real-time video streams. Using a VGG16-based model, this project combines deep learning and some fancy boun…

Sentiment analysis using NLP techniques on Amazon product reviews. It covers text pre-processing, visualization, and basic sentiment classification.

how to implement Transfer Learning using the pre-trained ResNet50 model to classify different types of flowers

This repository demonstrates how to build, train, and evaluate a Convolutional Neural Network (CNN) using TensorFlow and Keras for image classification. The project covers all essential steps, from…

How to build, train, and evaluate a Generative Adversarial Network (GAN) for generating fashion images. The project covers all essential steps, from model building to training and evaluation.

comparison of different machine learning models such as GB, XGB and NN to see which performs better at real time SYN flood detection