Add MovieLens.load to parse and encode the movielens dataset (#947)

This adds a `load` function that returns:

- a StellarGraph containing the users (with IDs `u_...`), and movies (IDs
  `m_...`) as well as "rating" edges, where the features in the users nodes have
  been encoded and normalised
- a pandas DataFrame containing the edges (as in `user_id` and `movie_id`) and
  their rating label to use for training/testing

Example first few rows of each file for reference:

`u.data`:
```
196	242	3	881250949
186	302	3	891717742
22	377	1	878887116
```

`u.item`:
```
1|Toy Story (1995)|01-Jan-1995||http://us.imdb.com/M/title-exact?Toy%20Story%20(1995)|0|0|0|1|1|1|0|0|0|0|0|0|0|0|0|0|0|0|0
2|GoldenEye (1995)|01-Jan-1995||http://us.imdb.com/M/title-exact?GoldenEye%20(1995)|0|1|1|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0
3|Four Rooms (1995)|01-Jan-1995||http://us.imdb.com/M/title-exact?Four%20Rooms%20(1995)|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0
```

`u.user`:
```
1|24|M|technician|85711
2|53|F|other|94043
3|23|M|writer|32067
```

See: #812