ELEC-E7260 - Machine Learning for Mobile and Pervasive systems D, Lecture, 12.1.2022-13.4.2022

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Understanding of good practices for machine learning with noisy and inaccurate data; feature extraction/ feature subset selection, handling high dimensional data, ANN + Deep Learning, Probabilistic graphical models, Topic models; as well as Unsupervised learning and clustering, Anomaly detection and Recommender systems.

Credits: 5

Schedule: 12.01.2022 - 13.04.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Stephan Sigg

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Examination, Assignments and group works

Workload

  • valid for whole curriculum period:

    Contact hrs 26 h
    Independent work 84 h

DETAILS

Study Material

  • valid for whole curriculum period:

    Lecture handouts/slides,

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    4 Quality Education

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III-IV

    2021-2022 Spring III-IV

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=ELEC-E7260

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    WebOodi

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Aalto University Code of Academic Integrity and Handling Violations Thereof