Diabetes mellitus, commonly known as diabetes is a metabolic disease that causes high blood sugar. The hormone insulin moves sugar from the blood into your cells to be stored or used for energy. With diabetes, your body either doesn’t make enough insulin or can’t effectively use its insulin.

Predicting the incidents raised by the customer

This project develops an activity recognition model for a mobile fitness app using statistical analysis and machine learning. By processing smartphone sensor data, it extracts features to train models that accurately recognize user activities.

SVM, Logistic Regression, K-Nearest Neighbors Classifier, GaussianNB, Random Forest, XGBoost, DecisionTree Classifier, Ensembled Classifier, ExtraTrees Classifier, Voting Classifier

Implementing a Generic Decision Tree Classifier in Swift and comparing it with a python version.

Data Science final project

Machine Learning Recipes is a series of videos from Google Developers covering codes (python) and insights about ML.

This project used machine learning concept to predict disease on their symptoms

A parser for scikit-learn exported text models to execute in the Java runtime.

This repo contains the Minor Project 1 named Fasal Fusion: An Algorithmic Approach to Transform Crop Recommendations

In this project I intend to predict customer churn on bank data.

Predicting Tags for Stack Overflow

Different models to detect if a claim is fraudulent or not

This is my own code. The data set is taken from Kaggle competitions. Here is the link: https://www.kaggle.com/competitions/titanic

Interconnect : Clients Churn Prediction using ML

Decision tree classifier to predict the right classes of the observations in the 'Iris' data set.

This is the Data Mining Project for predicting the student's grade before the final and Mid-2 examination. I use Python and Jupyter Notebook for this Project.

A crop recommendation website which uses an ML model (decision tree classifier) to recommend the crop that can be grown in a particular area

Code templates for data prep and different ML algorithms in Python.

Machine Learning lessons (Linear Regression, Logistic Regression, DecisionTreeClassifier, SVC, RandomForestClassifier, K Clustering, Naive Bayes) and data manipulation codes learned from this playlist: https://www.youtube.com/watch?v=gmvvaobm7eQ&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw&index=1