Overview
The structure of the course is as follows:
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A number lectures. Information can be found on the page’s menu or at timetable. This includes an overview of up and coming deadlines.
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4 short practical Python notebooks on how to use scikit-learn, numpy, pandas, Matplotlib and other tools that are essential for real machine learning projects in Python.
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4 short theoretical Python notebooks on aspects of machine learning.
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An ongoing project. You will be using a real data set, and the idea is that you try the techniques that you learn during the course on the project. At the end of the project you are to write a short report on the methods you have tried and the results that got.
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An exam.