✋🏼🛑 This one stop project is a complete COVID-19 detection package comprising of 3 tasks: • Task 1 --> COVID-19 Classification • Task 2 --> COVID-19 Infection Segmentation • Task 3 --> Lung Segmentation

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

Landscape of ML/DL performance evaluation metrics

A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS

Evaluating machine learning methods for detecting sleep arousal, bachelor thesis by Jacob Stachowicz and Anton Ivarsson (2019)

calculate ROC curve and find threshold for given accuracy

Analytical tool to help the company decide whether the employee will stay or not

A dataset containing over 70,000 data points, 12 features, and one target variable were used to analyze if machine learning could predict if an individual has cardiovascular disease.

INN Hotels Project

Détecter les faux billets à partir du jeu de données englobant statistiques sur 6 caracthéristiques des billets

Udacity DSND capstone project on the Bertelsmann-Arvato challenge on customer segmentation report and supervised learning model.

The objective of this capstone project is to use Natural Language Processing (NLP) to create a machine-learning model that predicts the quality of questions posted on Stack Overflow, a popular question-and-answer platform for software developers.

This problem is a typical Classification Machine Learning task. Building various classifiers by using the following Machine Learning models: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), XGBoost (XGB), Light GBM and Support Vector Machines with RBF kernel.

This code includes reading the data file, data visualization, variable splitting, model building, prediction and different metrics calculation using knn.

Decision Tree classifier using Logistic Regression

Credit card fraud refers to any unauthorized or fraudulent use of someone else's credit card information to make purchases or obtain funds. It is a criminal activity and a form of identity theft. This repository contains an implementation of a credit card fraud detection system using machine learning techniques.

Supervised Classfication models - Logistic Regression & Decision Tree, AUC-ROC Curve

Continuing with telemarketing model to predict campaign subscriptions in a portuguese bank institution. For this project I have evaluated the performance of four resampling techniques and selected the best one to implement the logistic model.