Machine learning is a way for computers to predict information based on the data we given to them. Machine learning can do three main tasks: Regression, Classification and Clustering.
Regression: Generates a continuous value (e.g. -1.1, 2.09, 20) from given data.
Classification: Generates a discrete value (e.g. 1, 2, 3), mainly for classifying given data.
Clustering: Generates centroids (center of data) based on the given data and predict which centroids that a data belongs to.
It is a more advanced version of machine learning. The training techniques are significantly improved and models are more complex compared to machine learning.
LinearRegression:
Make prediction on how long will a player reach certain level
Spawn an enemy where the difficulty is based on input
LogisticRegression:
Make an enemy that makes decision between 2 choices (e.g. fighting and running)
Detect hacking players
KMeans:
SupportVectorMachine
In machine/deep learning, we mainly need to do training before we can predict things. To train, we need a lot of data and choose the correct models so that we can achieve very good results. Once training is done, you can use the model to predict values based on the data that was never seen before by the model.