Deep Learning vs Tranditional ML methods for TB Drug Resistance prediction from Genomic data

[Modeling] Project in 2022 - Simple Model of important factors in the incidence of heart disease and prediction model

Introduction to cross-valdation in Machine Learning, with coding examples for supervised classification.

Performed univariate and bivariate analysis to understand the features and their relationships for loan approval prediction. Achieved highest accuracy of 98% for Extreme Gradient Boosting among all tested machine learning classification models.

Object detection exercise for the Neural Networks for Computer Vision course. Using stratified KFold for data with multiple labels and instances, and self-implementation of mAP with multiple configurations.

Malicious URL detector built with deep exploration on feature engineering.

Machine Learning App in R for predicting whether a newly released movie will be a hit or a flop. Practically useful for streaming services and cinemas.

Zindi hackathon

Machine learning prediction project, 2019.

Fundamentals of Machine Learning Assignment Repository

Applying Convolutional Neural Networks (CNN) for recognizing manuscript digits.

Mithilfe von Machine Learning und Open Data zu Unfällen in Berlin (2018-2021) beantworten wir folgende Frage: Was sind die wichtigen Faktoren/Einflüsse auf Unfallgefahr? Und wie gut lässt sich damit die Unfallschwere überhaupt vorhersagen?

Data sampling library

This project consists in using machine learning to analyze the factors that affect wine quality and in building a model for predicting it. The model was tested on unseen wines to evaluate its accuracy.

This project aims to understand and implement all the cross validation techniques used in Machine Learning.

Data-Sprint-61---Meteorite-Threat-Identification-challenge using StratifiedKFolds and Manual Hyperparameter tuning of the algorithm

使用比赛方提供的脱敏数据，进行客户信贷流失预测。