Decision Trees vs Random Forests, Explained by Natassha Selvaraj via @kdnuggets

A simple, non-math-heavy explanation of two popular tree-based machine learning models.

I liked this which was nice and easy to understand if you aren't great at maths and formulas.

Decision Tree Algorithm, Explained by Nagesh Singh Chauhan via @kdnuggets

All you need to know about decision trees and how to build and optimize decision tree classifiers.

A very clear and easy to understand guide that you might want to share with any folks that need the detailed information in it.

A Guide to Decision Trees for Machine Learning and Data Science by @GeorgeSeif94 via @kdnuggets

What makes decision trees special in the realm of ML models is really their clarity of information representation. The “knowledge” learned by a decision tree through training is directly formulated into a hierarchical structure.

Bookmark this so you can refer back to it when needed. Add him in Twitter for some great help and information too.

WEBINAR: Scaling Big Data Pipelines in Apache Spark, No Coding Required - 15 November 2018

Various companies across multiple industries collect and house vast amounts of data. However, most face the same challenge: the ability to process big data and quickly find insight within its framework. Introducing KnowledgeSTUDIO with Apache Spark, the ultimate solution for both data scientists and data analysts. The graphical user interface with Big Data capabilities allows organizations to build pipelines seamlessly. Topic: Scaling Big Data Pipelines in Apache Spark, No Coding Required Date: Thursday, November 15, 2018 Time: 2 p.m. ET/11 a.m. PT Datawatch Speakers: Dr. Steve Walker, Sr. Data Scientist and Mike Rowley, Product Director   Join us and learn how users of KnowledgeSTUDIO for Apache Spark, a wizard-driven productivity tool for building Spark workflows, have overcome these challenges. Learn how data science teams can:  Utilise interactive workflows with an automated design canvas for building, displaying, refreshing, and reusing analytic models   Automatically generate code that can be customised and incorporated into production scripts   Include manually written code within the graphical workflow   Leverage advanced modelling with open source packages such as Spark ML, Spark SQL   Avoid overhead costs of parallelisation when datasets are very small   Build, explore data segments, and discover relationships using patented Decision Tree technology REGISTER NOW

How decision trees work by/via @_brohrer_

This is a fantastic overview of how decision trees work by Brandon Rohrer. Includes lots of diagrams, easy to follow descriptions and a short video if you'd rather watch.

I love that it tells you what to look out for so that you hopefully won't fall into some of the common pitfalls.  I really suggest you look at his other blog entries which are incredibly useful and worth bookmarking.