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Machine learning model with linear regression (Ridge regression) and standardscaler using sklearn module using the Algerian forest fire dataset with flask to open a webpage to add new data for prediction.
Telecom Customer Churn Prediction This repository contains a machine learning project focused on predicting customer churn in the telecommunications industry. By leveraging a dataset of customer demographics and usage patterns, we develop and deploy a predictive model to identify customers at risk of leaving the service.
In this project I built machine learning models using Multiple Linear Regression, Ridge regression, Lasso regression, Elasticnet regression and then created a pickle file of the regression model which gave best accuracy
This project involves predicting phishing URLs by extracting 17 features across three categories. It entails training and testing machine learning models using a dataset sourced from Phishtank.
This Repository Contain All the Artificial Intelligence Projects such as Machine Learning, Deep Learning and Generative AI that I have done while understanding Advanced Techniques & Concepts.
This groundbreaking prediction system utilizes extensive data and predictive algorithms to forecast the health effects of smoking and drinking habits. By analyzing individual behaviors, it offers tailored insights to empower proactive health decisions.
This repository documents my journey to become a Machine Learning Engineer. It contains the list of projects undertaken, books read, courses pursued and almost everything I did in the process. So follow along or diverge to you own path, each way, I believe this will add value to any data professional / enthusiast.
A comprehensive suite of Python-based machine learning models for predictive analytics, employing different evolutionary algorithms for data analysis across various topics.
A topic-wise collection of mini projects implementing basic machine learning concepts through python. Originally implemented in Google colab notebooks.
. The proposed application, "MelanomaDetector," utilizes a Convolutional Neural Network (CNN) model, specifically a modified version of the VGG16 architecture pre-trained on the ImageNet dataset, for accurate melanoma detection