Helpful Links.md

Course glossary and lookup file

• Useful snippet collection for most problems you will encounter

Winning submissions

Week 1

• Excel Neural Net

Week 2

• No ML by Team 8
• Best ML approach

Week 3

• Xception bottleneck

Presentations

• Week 2 - ML in the value chain
• Week 3 - The goal of ML

Python:

• Beginners Cheat Sheet

• Lists cheat sheet

• Lists tutorial

• Dictionaries cheat sheet

• Dictionary tutorial

• If statement and Loops cheat sheet

• Loops tutorial

• If statement tutorial

• Functions sheet sheet

• Functions tutorial

• Classes cheat sheet

• Classes tutorial

• Jannes Python Session 1

• Jannes Python Session 2

Pandas:

• Pandas cheat sheet
• 10 minutes to Pandas tutorial
• Data analysis with Python tutorial
• Introduction to Pandas datastructures
• Common excel tasks demonstrated in Pandas

Numpy

• Numpy quickstart tutorial
• CS231n Numpy tutorial

Kaggle

• How to use Kaggle Kernels
• Kaggle progression system

Structured data tutorials

• Machine learning tutorial for beginners
• Exploring Survival on the Titanic
• A journey through Titanic

Jupyter notebooks

Note that the course does not require you to set up Jupyter notebooks as everything runs in the cloud.

• Getting started with jupyter notebooks

Google Colab

• Videos explaining Colab and the most important bash commands
• Colab overview with many helpful links

Other good DL courses

• Fast AI
• CS231n: Convolutional Neural Networks for Visual Recognition (Stanford)
• Andrew NG Machine Learning on Coursera