Intro to Machine Learning

Machine Learning in simple word, is trying to ask machine to deduct something based on data, lots of data.

Based on this data, model is created by algorithm.

argmax return value of a variable that maximise the function.

Machine learning is about:
* turn raw data into feature vectors
* analyse the feature and try different algorithm to come up with the model
* try the model
* rinse and repeat

Type of machine learning:
* supervised vs semisupervised vs unsupervised
supervised have training data.
* online vs batch
online; means it can be done on the go. while batch is offline
* instance-based vs model-based
instance-based; learn by heart. comparing it to the learned example
model-based; build the model from example. then use the model to predict

Overfitting
the model is good for the training set; but it is not good for test data

Underfitting
the model is not good for the training set.