Recruiting and retaining drivers is seen by industry watchers as a tough battle for Ola. Churn among drivers is high and it’s very easy for drivers to stop working for the service on the fly or jump to Uber depending on the rates.

Given a set of attributes for an Individual, determine if a credit line should be extended to them. If so, what should the repayment terms be in business recommendations?

A personal project where logistic regression is used to predict if a student dropped out.

Python framework to evaluate Named Entity Recognition (NER) models. Creates entity-level confusion matrix and classification report.

The script will display a heatmap showing the performance metrics (accuracy, precision, recall, f1-score) of the learning models: K-nearest neighbors, Random Forest, Support vector machine and Multilayer perceptron. If you choose to display confusion matrices, they will be plotted for the chosen model.

This includes various assignments I worked on learning Data Mining in R Studio

Developed a predictive model to classify individuals into one of seven weight categories (ranging from insufficient weight to obesity type 3) based on various personal factors using diverse neural network architectures.

This project leverages Random Forest Classification to predict heart disease based on clinical parameters such as age, sex, blood pressure, and cholesterol levels. It achieves high accuracy and provides insights into feature importance, aiding early detection and prevention of heart disease.

This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras. The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.

Data Science Project - Full Depth analysis AND Prediction Using Decision Tree and Random Forest

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.

Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

Using the XGBClassifier from sklearn to predict whether or not patients have Parkinson's. Model is trained and tested on the UCI ML Parkinson's dataset.

Using information retrieval to help an emerging local artist boost its streams

Multi-class confusion matrix library in Python

🎓 Quais são os atributos determinantes no abandono estudantil? Isso é o que esse projeto visa descobrir 😎!

Classification model for Fashion MNIST dataset

Explore hands-on machine learning projects, resources, and collaborative opportunities in this GitHub repository.

To detect heart disease using machine learning

Comparing the performance of MLP (multilayer perceptron) and CNN (convolutional neural network) on USPS dataset and visualizing it via TensorBoard.