Topic outline

  • Assignments

    The course includes five sets of assignments. Each assignment consists of small coding tasks that require you to apply ML methods (provided by Python libraries such as "scikit-learn") to different datasets (such as weather data).

    The assignments are in the form of Jupyter notebooks at http://jupyter.cs.aalto.fi, where they are also to be submitted. After logging in with your Aalto credentials, choose the CS-C3240 Machine Learning, Autumn 2022 server. When it is started, you will see your own personal files.

    For a quick intro to Python and how to use numpy arrays, we refer to the excellent material at https://aaltoscicomp.github.io/python-for-scicomp/python/

    Remember to press the Submit button on JupyterHub to hand in the assignment! See "Assignment instructions" for details.


    		 ReleasedDeadline
    		 Lecture
    		Topic
    Assignment 1
    		Fri 9.9.2022Thu 15.9.2022, 23:59
    		 1 and 2
    		Introduction, regression
    Assignment 2
    		Wed 14.9.2022Thu 22.9.2022, 23:59
    		 3 and 4
    		Classification, feature learning, visualization
    Assignment 3
    		 Wed 21.9.2022Thu 29.9.2022, 23:59
    		 5 and 6
    		Non-parametric methods, deep learning
    Assignment 4
    		 Wed 28.9.2022Wed 12.10.2022, 23:59
    		 7 and 8
    		Clustering, probability theory
    Assignment 5
    		 Fri 7.10.2022Sun 16.10.2022, 23:59
    		 9 and 10
    		Reinforcement learning


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