The purpose of this project's design, development, and structure is to create an end-to-end Machine Learning Operations (MLOps) lifecycle to classify an individual's level of obesity based on their physical characteristics and eating habits.

A Data science app to predict who in Africa is most likely to have a bank account?

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.

Helping Farmers make informed decisions with Machine Learning ! 👩‍🌾🚜

Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform

In this project we try to predict home credit default risk for clients. We try to predict, if the client will have payment difficulties or not.

A machine learning model to predict whether a customer will be interested to take up a credit card, based on the customer details and its relationship with the bank.

Développer un modèle de scoring de la probabilité de défaut de paiement du client pour étayer la décision d'accorder ou non un prêt à un client potentiel.

Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer

The problem that this case study is dealing with predicts the location that a user is most likely to book for the first time. The accurate prediction helps to decrease the average time required to book by sharing more personalized recommendations and also in better forecasting of the demand. We use the browser’s session data as well as the user’…

Maximizing Revenue with Individualized Coupon Optimization Using Tree-Based Models

NLP Workshop -ML India

Anomaly Detection with Multiple Techniques using KDDCUP'99 Dataset

Example using Optuna to tune hyper parameters for LightGBM

FastAPI backend for CropFusionAI

CS5228 Kaggle Inclass Competition: Predicting if Income > 50K

The goal of this project is to predict the expression on the face. The expression labels are standard ones used in psychology research: angry, disgusted, fearful, happy, sad, surprised, neutral.

Photometric light curves classification with machine learning