Developed ML/DL based a web application for stock price prediction based on real-time data.

This will help you to prepare Machine learing and NLP exam of LPU. It's include ETE @ paper and all hand witten notes and recomented mcq.

This project involves building an Artificial Neural Network (ANN) for predicting customer churn. The dataset used contains various customer attributes, and the ANN is trained to predict whether a customer is likely to leave the bank.

As a DevOps and Machine Learning Enthusiast, dedicated to gaining expertise in cutting-edge technologies that will shape the future of the industry. With a passion for innovation and problem-solving, also committed to continuous learning and professional development I am a motivated and versatile individual, always eager to take on new challenges.

Pizza Order and bill calculator python project

This project is an AI-powered content generation tool that leverages Hugging Face's models to create customized content based on user queries. The application is built using Streamlit and provides an interactive UI for generating content tailored to different age groups and task types.

This repository contains the code implementation for the project "Brain Tumor classification Using MRI Images." The project aims to enhance brain tumor diagnostics through the utilization of Machine Learning (ML) and Computer Vision(CV) techniques, specifically employing a Support Vector Machine (SVM) classifier.

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Computer Vision INT345 handwritten notes and end term Paper and MCQ for practice

Malicious URL Detection is designed to identify potentially harmful URLs using machine learning techniques. The model leverages various features of URLs to classify them as malicious or benign, providing an essential prediction for cybersecurity.

Hi 🙋, I'm Vishal Lazrus there is information about me.

This project focuses on the segmentation of brain tumors in 3D MRI images using Convolutional Neural Network (CNN) models. The research compares the performance of SegNet, V-Net, and U-Net architectures for brain tumor segmentation and evaluates them based on complexity, training time, and segmentation accuracy.

Click below to checkout the website of this ML-NLP Project