Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.
Courses
Number
Title
Hours
Lecturers
227-0085-47 P
P&S: Machine Learning on Smart Phone
Does not take place this semester. Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account): https://psapp.ee.ethz.ch/ Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitagmittag im Semester möglich.
To access the offer and to enroll for courses log in (with your n.ethz account): https://psapp.ee.ethz.ch/ Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester.
3 hrs
Catalogue data
Abstract
The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
Learning objective
Machine Learning with Smart Phone Sensors –Programming Android Phones – Neural Networks – Keras/Tensor Flow- Projects and App on smartphones
Smartphones have several sensors that can acquire much useful information, for instance where we are, what we are doing, with whom we are together, what is our constitution, what are our needs. Based on this information our 'smartphone' offers us the appropriate computational power to process them in loco without sending the sensor data to the cloud. This course focus on giving the bases of machine learning and embedded systems. The student will learn the tools to implement a machine learning algorithm, such as Tensor Flow and others in their android phones to have an advanced smartphone. The course will end with 4 weeks project where the students can target a specific application scenario. It is not required any previous experience In machine learning. Phyton is a plus but the basis of phyton will be given in the course to be able to complete the project. The course will be taught in English and organized by the new Project-based Learning center.
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
: Special students and auditors need a special permission from the lecturers