Course Plan and Setup

PART I - preferably finished before March 13

Session	Responsible	Day/time 10:15-12:00. Tuesdays in Lab F and Fridays in Lab D.
Chapters 1-2 + software setup	Carolina	only online
Chapter 3 - Classification	Frida	31/1
Chapter 4 - Training Models	Birgitta	4/2
Chapter 5 - SVMs	Harry	7/2
Chapter 6 - Decision Trees	Nils	11/2
Chapter 7 - Ensemble learning and Random Forests	Johan	18/2
Chapter 8 - Dimensionality Reduction	Olle	25/2
Chapter 9 - Unsupervised Learning Techniques	Carolina/Bo	3/3
Presentations		13/3

See ML Competition - wohoo! for info on the final project of PART I.

PART II

Session	Responsible	Date	Zoom link
Chapter 10 - Intro to ANNs with Keras	Frida	Wed, 22/4 (13:15)	Join Zoom Meeting https://lu-se.zoom.us/j/67738747987 Links to an external site. Meeting ID: 677 3874 7987
Chapter 11 - Training DNNs	Birgitta	Mon 4/5 13:15	Join Zoom Meeting https://lu-se.zoom.us/j/61358908993 Links to an external site. Meeting ID: 613 5890 8993
Chapter 12 - Custom Models and Training with TensorFlow apart from discussing the theory we'll also walk through the following: https://colab.research.google.com/github/ageron/handson-ml2/blob/master/12_custom_models_and_training_with_tensorflow.ipynb Links to an external site.	Johan O	Friday 15/5 13:15	Join Zoom Meeting https://lu-se.zoom.us/j/63216970807 Links to an external site. Meeting ID: 632 1697 0807
Chapter 13 - Loading and Preprocessing Data with TensorFlow	Harry	Mon 25/5 15:15	https://lu-se.zoom.us/j/66649497383 Links to an external site.
Chapter 18. Reinforcement learning	Olle	Wed, 3/6 13:15	TOPIC: Hands-on ML: Reinforcement session WHEN: Jun 3, 2020 01:15 PM Stockholm WHERE: LU Zoom meeting: https://lu-se.zoom.us/j/65137095018
Project Ok the football game thread is on canvas		Tue, 16/6 13:15	WHERE: LU Zoom meeting: https://lu-se.zoom.us/j/63415773816?pwd=SVhKQTFwR0tvWFpsbmxhL0tCbmREZz09 Links to an external site.

Part III Fridays 13:15-15:00

Session	Responsible	Date	Zoom link
Chapter 14 - Deep Computer Vision Using CNNs	Frida	Nov 13	https://lu-se.zoom.us/j/62901988018?pwd=eUNDdzBEZmZEdy9veGYrYTY5dUdhdz09 Links to an external site.
Chapter 15. Processing Sequences using RNNs and CNNs	Johan and Harry	Nov 27	https://lu-se.zoom.us/j/62901988018?pwd=eUNDdzBEZmZEdy9veGYrYTY5dUdhdz09 Links to an external site.
Chapter 16. Natural Language Processing with RNNs and Attention	Pex	Dec 11	https://lu-se.zoom.us/j/62901988018?pwd=eUNDdzBEZmZEdy9veGYrYTY5dUdhdz09 Links to an external site.
Chapter 17. Representation learning and Generative Learning using Autoencoders and GANs	Olle	Jan 19 - 13:15	https://lu-se.zoom.us/j/63561985218?pwd=K2dXUkF6QlA3bkREdlNndjJsR0xVdz09 Links to an external site.
Chapter 19. Training and Deploying TensorFlow Models at Scale or Seminar by experts	TBD	TBD
Project

Each participant will be made responsible for 1-2 Chapters/Sessions (depending on the number of participants).

Tasks for the responsible:

go through the chapter devoted to your session
create a session page here on canvas: include a summary, interesting observations, additional references as well as an agenda for the discussion session. Finalized at least 24 h before the session.
lead the session

Tasks for remaining participants:

Time needed and course credits (preliminary):

PART I:

Participant: 8h/session

Responsible: 16h/session

Competition: 24h

In total 8 sessions, out of which you were responsible for 1: 7*8+16 = 72 h

total: 72+24 = 96 h ~ 4 hp

PART II:

Participant: 8h/session

Responsible: 16h/session

In total 5 sessions, out of which you were responsible for 1: 4*8+16 = 48 h

Project: 40h

total: 48+40 h = 88 h ~ 3 hp

PART III

Participant: 8h/session

Responsible: 16h/session

In total 5 sessions, out of which you were responsible for 1: 4*8+16 = 48 h

Project: 36h

total: 48+36 h = 88 h ~ 3 hp

In TOTAL total: 10 hp

*1 credit equals 27 hours of work. source: https://www.lth.se/english/study-at-lth/masters-programmes-in-english/ects/