This book provides a non-mathy entry point in to the world of decision trees and random forests. Chapter 1 introduces the three kinds of learning algorithms: Supervised Learning Algorithm: The algo feeds on labeled data and then use the fitted algorithm on unlabeled data Unsupervised Learning Algorithm: The algo feeds on unlabeled data to figure out structure and patterns on its own Semi-Supervised Learning: The algo feeds on labeled and unlabeled data.

Context I stumbled on this book on my way to Yangon and devoured the book with in a few hours. It took me more time to write the summary than to read the book. The book is 300 pages long and full credit goes to the author for making the book so interesting.In this post, I will attempt to summarize the contents of the book. This book is a fascinating adventure into all the aspects of the brain that are messy and chaotic.

Most of the decisions that we take or activities that we do, on a daily basis are not a result of deliberate thought. These are the result of habits that we have built over time. We realize some of these decisions/activities as habits but often carry out many activities in auto-pilot mode. This is good as it frees our mind to do other things. The flip side is that we do not seem to be in control of the actions and hence feel powerless.

The paper titled, “Making Covariance-Bassd Portfolio Risk Models Sensitive to the Rate at which Markets Reflect New Information”, makes a case against using any GARCH type of volatility estimate for portfolio risk estimation. Instead it suggests a simple way to incorporate changes in the level of implied volatility of the options in to the computation of risk of a portfolio comprising underlying securities. The following is a brief summary of the paper :

Neo4j’s founder Emil Eifrem shares a bit of history about the way Neo4j was started. Way back in 1999, his team realized that the database that was being internally used had a lot of connections between discrete data elements. Like many successful companies which grow out of a founder’s frustration with status quo, Neo4j began its life from the founding team’s frustration with the fundamental problem with the design of relational databases.