Feature Scaling

Let us then use MinMaxScaler, a module from sklearn library to scale the values into the range of 0 and 1. More about it here

We shall do this feature scaling as follows:

Use fit_transform to transform features by scaling each feature. We shall do this fitting on the train data train_data.
Then, use the transform method on the same scaler to transform the values of val_data and test_data.

INSTRUCTIONS

Import MinMaxScaler from sklearn.preprocessing

from sklearn.preprocessing import << your code comes here >>

Get the MinMaxScaler object scaler and put feature_range=(0,1).
```
scaler = << your code comes here >>(feature_range=(0, 1))
```
Use fit_transform method of scaler to apply feature scaling on train_data. Store the result in train.
```
train = scaler.<< your code comes here >>(train_data)
```
Use transform method of scaler to apply feature scaling on val_data. Store the result in val.
```
val = scaler.<< your code comes here >>(val_data)
```
Use transform method of scaler to apply feature scaling on test_data. Store the result in test.
```
test = scaler.<< your code comes here >>(test_data)
```

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