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

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

Tic-Tac-Toe Q-Learning is a beginner-friendly example of using reinforcement learning.

Covid informetion website.

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.

Parkinsons-Disease-Detection This is a project which predicts whether a person have Parkinson's Disease or not

Password Generator python mini project

This project focuses on building a powerful image classification model to distinguish between cats and dogs using a Convolutional Neural Network (CNN)

Explore Linear Algebra & PCA. Python PCA visualizations for dimensionality reduction. Solved 2x2 & 3x3 matrix problems for practical understanding. Ideal for learners & professionals. Strengthen your math skills today!

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

Choosing the right estimetor/algorithm for our problem

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

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

DevOps, Docker, Kubernet, ingress, reddit-webapp and aws project

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.