Machine-Learning

In this repository, you can find several Machine Learning Projects that I have undertaken. Each project uses a different dataset and focuses on a different machine learning topic. Projects that are of a smaller scale are located under the folder "Small-scale Projects" while projects of a larger scale are located under the folder "Large-scale Projects".

Small-scale projects are projects with implementation of one or two types of models, with emphasis on the exploration and study of each model type. On the other hand, large-scale projects are projects that explores a wider range of machine learning topics, covering more than three types of models. For more information of each small-scale and large-scale project, please refer to their respective readme file in their corresponding folder.

The following table indicates the corresponding machine learning topic to each dataset used:

For Small-scale Machine Learning Projects

Dataset	Machine Learning Topic
UCI Machine Learning Repository - Bike Sharing Dataset	Regularized Linear Regression
UCI Machine Learning Repository - Seeds Dataset	Logistic Regression
UCI Machine Learning Repository - Online Retail Dataset	Topic Modelling
Microchip Quality Assurance Dataset	Gaussian Naive Bayes & Multi-class Classification

For Large-scale Machine Learning Projects

Dataset	Machine Learning Topic
Various Datasets for Apartments, Condominiums and Executive-Condominiums in Singapore	Multivariable Linear Regression; Regression Tree (Decision Tree); Ensemble Trees (Random Forest, Gradient Boosting Regressor & Extreme Gradient Boosting Regressor)

samtwl/Machine-Learning

Machine-Learning

For Small-scale Machine Learning Projects

For Large-scale Machine Learning Projects

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