Exploratory data analysis and predicting diabetics using PySpark

This project involved exploring object classification using machine learning models from scikit-learn, with a focus on dimensionality reduction to simplify data complexity. Additionally, a comprehensive data narrative was created to illustrate the process and insights gained, utilizing Python libraries for data analysis and visualization.

This repository contains code for building a K-Nearest Neighbors (KNN) model to predict diabetes based on patient data. Includes data cleaning, hyperparameter tuning, and evaluation metrics.

Explore network traffic analysis with Machine Learning! This project utilizes Decision Trees, Random Forests, and K-Nearest Neighbors (K-NN) to predict optimal actions for network sessions. We evaluate classifier performance in accuracy, precision, recall, and F1-score.

Predicting whether Lisbon MBA Toastmasters Club members have remained in the club or left it.

Part of my PhD thesis - a system for reconstruction of damaged AIS data, consisting of 3 stages: clustering, anomaly detection and prediction

This project employs machine learning to forecast housing prices in California. By scrutinizing location, housing details, and demographics, it constructs various regression models like Linear Regression, KNN, Random Forest, Gradient Boosting, and Neural Networks. These models offer invaluable insights to optimize predictive real estate investment

This project provides a comprehensive framework for evaluating classification models and selecting the best algorithm based on performance metrics. It demonstrates the importance of hyperparameter tuning and model comparison in machine learning workflows.

An Online Book Store built in java that also recommends Books based on user's favourite book using a machine learning model in Python integrated through a Flask API.

This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

Project aims to forecast potato prices in India using LSTM, KNN, and Random Forest Regression, integrating historical data on prices, regional stats, and rainfall patterns. Targeting agricultural stakeholders for informed decision-making.

Enhancing Patient Care through AI-Driven Disease Prediction

Plain python implementations of basic machine learning algorithms

Aplicação web onde você consegue treinar um modelo de Machine Learning para classificar uma pessoa como do sexo masculino ou feminino com base em seu nome.

Using k-nearest neighbors, and infinite-lookback ngrams with LLMs

This repository contains a Jupyter notebook that implements and optimizes several machine learning models on a dataset

This project provides the classification of DNA sequences for Breast cancer prediction which into promoter regions associated. Using machine learning and deep learning techniques, I analyze and try to predict sequence data for negative and positive answers in cancer prediction.

Exploring QSAR Models for Activity-Cliff Prediction

Comparison of k-Nearest Neighbors (kNN) and Logistic Regression Model performance

Tools created for machine learning classification model evaluation