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| Python Programming for Machine Learning is an optional course in the module "Machine Learning - Theory and Applications" and is worth 3 LP (3 ECTS credits). | Python Programming for Machine Learning is an optional course in the modules "Machine Learning 1", "Cognitive Algorithms" and "Machine Learning - Theory and Applications" and is worth 3 LP (3 ECTS credits). |
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| Track A is recommended for ML1 students as it has no time conflict with that course. | Participation in the exercise sessions is not mandatory but highly recommended. |
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| || '''Course Period:''' || TBA || ||<(^|2> '''Lectures:''' || TBA [Track A] || || TBA [Track B] || ||<(^|3> '''Exercises:''' || TBA [Track B] || || TBA [Track A] || || TBA || || '''Exam:''' || TBA || |
|| '''Course Period:''' || from Oct 15, 2018 to Nov 9, 2018 || ||<(^|2> '''Lectures:''' || [Track A] Monday 10:15 - 11:45 in EMH 225|| || [Track B] Monday 16:15 - 17:45 in H 2032|| || '''Exam:''' || Nov 15, 2018, 14:00 (presumably) || |
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| ||<(^|2>'''Trainers''' || Sergej Dogadov || | ||<(^|3>'''Trainers''' || Sergej Dogadov || |
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| ||'''Contact''' || sergej.dogadov@campus.tu-berlin.de || || '''ISIS:''' || TBA || |
|| David Lassner || ||<(^|2> '''Contact''' || philipp.seegerer@tu-berlin.de || || lassner@tu-berlin.de || || '''ISIS:''' || https://isis.tu-berlin.de/course/view.php?id=13921 || |
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* '''When does the course start?''' TBA |
* '''When does the course start?''' on Monday Oct 15th, 2018 at 16:15 [Track A] or 14:15 [Track B] |
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| '''Main Topics''' | Knowledge of elementary programming concepts will be helpful. Be aware that lack of such knowledge will increase the time demand of the class. |
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| * Python Basics * Numpy / Performance / Plotting * Rounding / Overflow / Linear Algebra * Randomness / Simulation |
Homework is submitted via ISIS (see above), therefore you have to register there. |
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| '''Additional Topics''' * Linear Models (Regression, PCA) * Low-Level Extensions (F2PY) Knowledge of elementary programming concepts will be helpful. Be aware that lack of such knowledge will increase the time demand of the class. In that case, you should consider to prepare with a python beginner class. Homework is submitted via the ISIS page. === students from other universities === |
=== Students from other universities === |
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| * pass by at my office (see above) to have them signed | * pass by at Mr. Dogadov's office (MAR 4.034) to have them signed |
Python Programming for Machine Learning
Python Programming for Machine Learning is an optional course in the modules "Machine Learning 1", "Cognitive Algorithms" and "Machine Learning - Theory and Applications" and is worth 3 LP (3 ECTS credits).
In the general case, it is not possible to take the Python course as a standalone course. There are possible exceptions to this (e.g. it complements another ML or related course you are taking in parallel). In that case, a special request needs to be made.
The course will be split in two tracks A and B, with the same content, but held at different times of the week/day. Students can opt for either of these.
Participation in the exercise sessions is not mandatory but highly recommended.
Course Period:
from Oct 15, 2018 to Nov 9, 2018
Lectures:
[Track A] Monday 10:15 - 11:45 in EMH 225
[Track B] Monday 16:15 - 17:45 in H 2032
Exam:
Nov 15, 2018, 14:00 (presumably)
Language:
English
Trainers
Sergej Dogadov
Philipp Seegerer
David Lassner
Contact
ISIS:
Frequently Asked Questions (FAQ)
When does the course start? on Monday Oct 15th, 2018 at 16:15 [Track A] or 14:15 [Track B]
How to register for the course? Pre-registration is not needed.
Knowledge of elementary programming concepts will be helpful. Be aware that lack of such knowledge will increase the time demand of the class.
Homework is submitted via ISIS (see above), therefore you have to register there.
Students from other universities
If you are not a student at TU and want to earn credit, you have to solicit ''Nebenhörerschaft'':
- print out the forms concerning Nebenhörerschaft you find on that page
- pass by at Mr. Dogadov's office (MAR 4.034) to have them signed
- in addition, the dean of faculty IV has to sign
- register at the the Campus Center. You will receive a TUBIT account (see below).