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Machine learning projects done as part of an online PGPML course offered by Great Learning, an ed-tech company.

Jupyter Notebook 100.00%
machine-learning statistical-learning applied-statistics supervised-learning unsupervised-learning ensemble-learning recommender-system feature-selection model-selection hyperparameter-tuning

pgpml-projects's Introduction

PGPML-Projects

This repository contains machine learning projects that I have implemented as part of an online Post Graduate Program in Machine Learning (PGPML) course offered by Great Learning during November 2019 to June 2020.

The repository folders are organized according to the machine learning module name and each folder consists of a problem statement document, a jupyter notebook and the dataset.

The ML modules covered are:

  • Applied Statistics (or Statistical Learning)
  • Supervised learning
  • Ensemble Techniques
  • Unsupervised learning
  • Featurization, Model Selection and Tuning
  • Recommendation Systems
  • Capstone project

Feel free to ask any queries regarding the projects through email (email-id: [email protected]).

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