References for Machine Learning and RCF
To learn more about machine learning and this algorithm, we suggest the following resources:

The article Robust Random Cut Forest (RRCF): A No Math Explanation
provides a lucid explanation without the mathematical equations. 
The book The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
provides a thorough foundation on machine learning. 
Random Cut Forest Based Anomaly Detection On Streams
, a scholarly paper that dives deep into the technicalities of both anomaly detection and forecasting, with examples.
A different approach to RCF appears in other AWS services. If you want to explore how RCF is used in other services, see the following:

Amazon Kinesis Data Analytics SQL Reference: RANDOM_CUT_FOREST and RANDOM_CUT_FOREST_WITH_EXPLANATION

Amazon SageMaker Developer Guide: Random Cut Forest (RCF) Algorithm. This approach is also explained in The Random Cut Forest Algorithm
, a chapter in Machine Learning for Business (October 2018).