Machine learning

Case study notes

Introduction

Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. This is important to our case study as it allows self-driving cars to learn from it’s environment and mistakes.

Terminology

1. Behavioural data
2. Cloud delivery models:
   1. Infrastructure as a service (IaaS)
   2. Platform as a service (PaaS)
   3. Software as a service (SaaS)
3. Cloud deployment models
4. Collaborative filtering
5. Content-based filtering
6. Cost function
7. F-measure
8. Hyperparameter
9. K-nearest neighbour (k-NN) algorithm
10. Matrix factorization
11. Mean absolute error (MAE)
12. Overfitting
13. Popularity bias
14. Precision
15. Recall
16. Reinforcement learning
17. Right to anonymity
18. Right to privacy
19. Root-mean-square error (RMSE)
20. Stochastic gradient descent
21. Training data

Examples

An excellent, and I truly mean excellent example is MarI/O, a machine learning program that learns how to play mario, and mario kart.

1. Super Mario World: https://www.youtube.com/watch?v=qv6UVOQ0F44
2. Mario Kart: https://www.youtube.com/watch?v=S9Y_I9vY8Qw
   

Devote time and attention to gaining knowledge of (an academic subject), especially by means of books