Machine learning

Case study notes

Introduction

Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks.[1] It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

The recommender problem

Estimate a utility function that automatically predicts how a user will like an item

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

Find an approximate value for an unknown quantity.