Week 1 - General Introduction

This week you will...

• get a basic introduction to neural nets in order to get a first intuition in the underlying mechanisms

• get a first idea about possible projects you might want to work on throughout the course

Learning Resources

7MB

251023_General Introduction.pdf

PDF

Open

44KB

Guidlines for Presenting Assignments.pptx

Open

• Video Neural Networks Explained (12 minutes)

• Introductory course on Python from Kaggle

• Tutorial on Colab on Medium

Until next week you should...

• Watch the following videos:

  • Machine Learning Explained in 100 Seconds (Fireship, 2:30 min)

  • What is a Loss Function? Understanding How AI Models Learn (IBM Technology, 10 min)

  • Backpropagation, intuitively | Deep Learning Chapter 3 (3Blue1Brown, 13 min)

  • Parameters vs Hyperparameters (Pankaj Kumar Porwal, 5:40 min)

  • Validation data: How it works and why you need it (Galaxy Inferno Codes, 5:40 min)

  • TensorFlow Tutorial 3 - Neural Networks with Sequential and Functional API (Aladdin Persson, 21 min)

  • TensorFlow Tutorial 14 - Callbacks with Keras and Writing Custom Callbacks (Aladdin Persson, 11 min)

• Think about project ideas to present in class next week (post your ideas in the chat during the week)

• Complete the two assignments given in the following notebooks:

  • Assignment Notebook 1

  • Assignment Notebook 2