Heart disease detection using Machine Learning

Create a machine learning model to predict if the policyholder will file a claim in the next 6 months or not based on the set of car and policy features.

Predict survival on the Titanic

Datamining concepts

Examined Chicago Car Crash data and created multiple models including logistic regression, KNN, Decision Tree and Random Forest. This project was to help identify what are the leading indicators to what may cause a car accident in Chicago.

Machine and Deep Learning Projects and basics

Advanced Machine Learning

Predict the activity category of a human.

A Python-based classification framework comparing Random Forest, Decision Trees, SVM, KNN, Logistic Regression, and Naive Bayes to predict individual income brackets

Some of my Machine Learning (SVM, Decision Trees, Random Forest, K Nearest Neighbors, Deep learning aka Neural Network, XGBoost) projects

This is a ML prediction model which predict personalized items for a particular customer

We built a music genre classification model using Random Forest and SVM. Accuracy: Random Forest ~54%, SVM ~56%.

A cybersecurity-focused machine learning project for detecting botnet activity using network traffic analysis and classification models.

Competición Kaggle: analizar clientes fugados y activos y entrenar un sistema que sea capaz de predecir si un cliente se ha fugado.

IDC 409 Web Scraping 2 Project

CNN-based method for movie genre classification from posters, with data pre-processing (one-hot encoding, missing values, imbalance, resizing). Performance compared to LeNet, AlexNet, VGG, ResNet-50, Logistic Regression, and Random Forest.

Digit recognizer with our own dataset

Heart disease classification project with different models (LogisticRegression, KNeighboursClassifier, RandomForestClassifier) and detailed reports.