# Introduction to Data Science, ML and Deep Learning - Deeplearning540

Mar 1 - 3, 2021 @ 2nd Terascale School for Machine Learning, https://indico.desy.de/event/28296/

HackMD Document for Group 5.

**Important:** Please be constructive, inclusive and positive in your communication with your peers.

## House Keeping

Some important links to not get lost:

### Video Conferencing

- the main zoom room is here: https://cern.zoom.us/j/66120916180?pwd=aWtSVWdUNFFXV1FFSFQ4MEFsK1RlQT09
- the team zoom room:
- team 5: William Korcari, David Brunner (replacing William on Monday) :https://cern.zoom.us/j/69440465856?pwd=S240cFBkckd1QXB5anRITUw5dTc3UT09

### Staying in Touch

- the main mattermost channel: https://mattermost.web.cern.ch/signup_user_complete/?id=j93uppzm6ff9zg5brdeuqobfgw
- https://mattermost.web.cern.ch/terascale-ml/channels/group-4
- team 5: William Korcari, https://mattermost.web.cern.ch

### Documenting Learning

Each team will have an individual hackmd document where they can collect notes and structure their learning. Here is a list of hackmd pads:

- team 1: Erik Buhmann, David Brunner https://hackmd.io/@2-Of0NO2QOuLytwFvbLLew/SyJQVqtzO/edit
- team 2: Sascha Diefenbacher, https://hackmd.io/@dYF1ZNaQQK6xeJntCK6kUA/rkVjaKUfu/edit
- team 3: Manuel Sommerhalder, https://hackmd.io/-qS2jfxpR9OoCXftYOUlOA?edit
- team 4: Mykyta Shchedrolosiev, https://hackmd.io/E6I1L96OQwSgTkyONCcMdw?edit
- team 5: William Korcari, https://hackmd.io/@Z3k-IRVbRJuDU-0M-Yfqzw/rJzE6f9fO/edit
- team 6: Tobias Lösche, https://hackmd.io/@loeschet/rkjPUMYGu/edit
- team 7: Jonas Rübenach, https://hackmd.io/@JKI5JOh-TG2m3ODr0QvHfw/Bk0KQTUfu/edit
- team 8: Oleg Filatov, https://hackmd.io/@tPZTWWavRMW6mtFiIrMjjA/H1m4DGtMd/edit
- team 9: Lucas Wiens, https://hackmd.io/@Q580EphDQTeemvMMuN-rpg/rkM1hEFz_
- team 10: Moritz Scham, https://hackmd.io/@lEufmOFkRq-7vjxuKEsn_Q/B1Z_LOIzu/edit

## Learning

Each lesson always follows the same structure and is expected to last about 1h. The teams need to self-organize the flow of the lessons.

1. learners watch the video :cinema:
2. learners answer at least one check-your-learning questions as a team (at best in a hackmd document) :heavy_check_mark:
3. learners dive into the exercise on their own if time permits :clock1:

:question: Instructors help with show stoppers like syntax errors where they can.
:computer: if you like to conduct the exercises, or code along during the videos, we suggest to use [google colab](colab.research.google.com/). Note, you may need a google account for this.

Each lesson has a jupyter notebook, that is half filled. The video lectures start from this notebook and provide content to fill in.

## Lessons

- Lesson 00: Preface
- Lesson 01: Diving into Regression [video](), [learner notebook](https://github.com/deeplearning540/lesson01/blob/main/lesson.ipynb)
- Lesson 02: Enter Clustering [video](), [learner notebook](https://github.com/deeplearning540/lesson02/blob/main/lesson.ipynb)
- Lesson 03: From Clustering To Classification [video](), [learner notebook](https://github.com/deeplearning540/lesson03/blob/main/lesson.ipynb)
- Lesson 04: Classification Performance ROCs [video](), [learner notebook](https://github.com/deeplearning540/lesson04/blob/main/lesson.ipynb)
- Lesson 05: Neural Networks as Code [video](), [learner notebook](https://github.com/deeplearning540/lesson05/blob/main/lesson.ipynb)
- Lesson 06: How did we train [video](), no jupyter notebook for this lesson
- Lesson 07: CNNs [video](), [learner notebook](https://github.com/deeplearning540/lesson06/blob/main/lesson.ipynb)
- Lesson 08: Deep Learning [video](), [learner notebook](https://github.com/deeplearning540/lesson07/blob/main/lesson.ipynb)