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Practical implementation and usage of machine learning algorithms, application of machine learning algorithms in real problems using Python. Notes are from Petri Valisuö's classes at University of Vaasa.

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Applied Machine Learning (AML)

Who?

These projects are based on the notes and experiments I conducted during Petri Valisuö's classes at the University of Vaasa.

Why?

The aim of this portfolio is to demonstrate my understanding of machine learning algorithms and their application to real-world problems. It serves as a showcase of my skills, experiments, and problem-solving abilities in the field of machine learning, Python, Numpy and Pandas.

When?

This portfolio was created during the Winter semester of 2023.

What?

This portfolio includes various machine learning projects using Python. It covers key topics such as:

  • Introduction to machine learning
  • Python basics for ML
  • Data reading, cleaning, and plotting
  • Preprocessing and feature extraction
  • Unsupervised machine learning for data exploration
  • Supervised machine learning
  • Model evaluation and optimization

How?

The projects demonstrate hands-on application of machine learning algorithms to solve real-world problems. The code is implements Python libraries such as Pandas and Numpy integrated in upyter Notebooks for each step in the learning process.

Deployment commands

poetry run jupyter-book build myfirstbook
poetry run ghp-import -n -p -f notebooks/_build/html

Useful guide for pubishing Jupyter Notebooks to GitHub Pages.

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Practical implementation and usage of machine learning algorithms, application of machine learning algorithms in real problems using Python. Notes are from Petri Valisuö's classes at University of Vaasa.

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