Customer churn prediction is the process of using machine learning models to identify customers who are likely to leave in the near future.

Our first participation in a Kaggle competition. Dry Beans Classification is an unranked competition held by ITI AI-Pro.

Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.

Predicts Forsyth–Edwards Chess Notation from a chess board image, using a C-SVC model

Data fetched by wafers is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not apparently obliterating the need and thus cost of hiring manual labour.

In this prototype, credit card approval data was analysed and a machine learning model was created to forecast the approval of credit card requests.

Predicting Diabetes with Machine Learning Techniques

This repository contains a machine learning project aimed at predicting diabetes using various algorithms such as Decision Tree Regression, Support Vector Regression (SVR), and Gaussian Naive Bayes (GaussianNB). Additionally, it provides a web deployment mechanism for the trained models, enabling easy access and utilization.

Heart Disease Predictor using Linear regression, Logistics and Support Vector Algorithm in Python.

Developed a Classification model that identifies personal attacks in Wikipedia comments using TF-IDF Vectorizer and LinearSVC with F1-Score of 0.97

iNeuron DataScience Internship: During this Internship, I have worked on project related to Data Analytics field in which logistic regression, decision tree and support vector machine have been used for classification problem

A Natural Language Processing Project: Use NewsAPI to gather URL's of news articles, along with webscraping, gather news articles and generate a bias classifier to then run on news sources that are considered "centered" by AllSides Media to determine the validity of that classification.

Demystify Cuisine and Culture From Ingredients using Natural Language Processing and Machine Learning | Python, Pandas, Matplotlib, NLTK, scikit-learn, webscraping, Python Flask-powered API backed by PostgreSQL, Front-end with HTML, CSS, and Javascript

Machine learning models to classify exoplanets from the raw dataset. Using Python: Sklearn, Joblib, NumPy, Pandas, Matplotlib.

Heart Failure prediction using machine learning python

ML API to perform OCR text extraction on receipt images and push the extracted then classified data to firebase.

An application which uses different algorithm for detecting Fraud Transactions.

Document classification using ML

Application of Machine learning to show acts of conspiracy, insider trading, and securities fraud in Enron dataset