Decision Trees and Random Forests: A Visual Introduction For Beginners: A Simple Guide to Machine Learning with Decision Trees Kindle Edition

Maybe, like me, you never got on with mathematics at school. In my schooldays, my problems in the subject were threefold: 1) a bad teacher 2) an active resistance to anything I didn’t find stimulating 3) a lack of awareness of how to work around dyscalculia. So instead, I challenged my teacher to prove things (he refused and/or was unable; this book in contrast does not resort to “it just works this way” explanations), I accused him of witchcraft when he produced correct numeric answers with no demonstration of how things worked, and I generally struggled with anything containing numbers.Here instead, everything is presented in a clear and simple fashion—as the title suggests, largely visual—minimizing the need to juggle a lot of numbers and instead working chiefly with concepts, which I can grasp much more readily. Where numbers are necessary, they’re not onerous and they’re nothing whose calculations one couldn’t do on a phone if necessary.In short, a clear and engaging primer in how probability trees and random forests work and, as a bonus, how they can be used in Python—as with other books in the series, again without expecting any deep knowledge of programming.If only books like this were used in schools, resulting in people better understanding stats and probability, the world might have a lot fewer problems than it does!

As a beginner to machine learning, and decision tree and random forest algorithms, this book was incredibly helpful and easy to understand. The applicability to everyday life is explained well in the sections of “Practical Uses” and gives real examples and how these algorithms are used in different scenarios.The process of creating both types of algorithms was also thoroughly explained and very helpful, and started out with hand-drawn algorithms that help the user contemplate different scenarios. It’s interesting that the human brain already does this without having to actively think about it, but the active thinking is what helps create the best possible outcomes to a given scenario. The explanations and decision-making algorithms explain the psychology of human behavior, and are helpful for both making and driving decisions.The illustrations really are helpful in describing the concepts, and also help you to find what you are looking for when needing to go back to a certain concept or explanation. I could see how this is definitely for a beginner, but out of the other things that I’ve looked into, this is the best place to start!

I wonder if one day we all start using algorithms for any decision we make in life. We can just have a simplified way to throw all variables in the decision-making mix and assign a task to a machine to perform it for us. At least then we will have machines to blame if the results of a decision don’t turn out as we expect them to! Jokes aside, this book is a pretty simple explanation of machine learning intended for beginners, which you will be able to use not only as a Python developer, but also to understand how trees and forests are used as a metaphor for the logical processes of machine learning.The example for Google driverless vehicles is used to explain how algorithms are used to help the machine analyze the data and come to logical outcomes. If you’ve never really touched upon computer algorithms, you may need to spend some more time in finding the parallel between machine and real learning. However, decision trees and random forests are just complex logical processes - sometimes our brains get into such analysis without even being aware of it. As inconvenient as it may seem, machines are better equipped to solve many problems. The book also goes into the common problems of decision trees and random forests, including practical training examples and visual presentation. It may now be an area for techies, but I think that in a few years, ML will be in the mainstream general knowledge. So. it’s good to get prepared!

Not bad at all but surprising typos affecting easy maths... It is too bad that such lack of qc costs 2 stars. The book is cheap, easy to read but instructive and corresponds to a couple of distracting evenings :-)

Just the initial thought of reading this book made me frustrated and stressed. But I was assured this book would be worth my time reading it, so I opened it up one rainy morning and read it. Although it is not the most exciting book to read, it was not as bad to read as I initially thought it would be. In fact, I actually found this book extremely helpful in deepening my understanding of complicated mathematics and complex algorithms. The visual aspect of this book was outstanding, and it is probably the biggest reason I was able to not freak out with stress while reading this book. The author, Chris Smith, did a great job keeping the complex information of the topic simple and concise. Even I, as a real beginner, was able to easily follow along and understand the topics. Suddenly, it all did not seem so complicated. And now that I read the book, I feel like I learned some valuable things I can use in my life!

Si te interesa conocer de un vistazo la teoria de los arboles de decision este pequeño libro des de gran ayuda

Es ist für Anfänger (ich bin kein Anfänger) und stellt Schritt für Schritt den Aufbau und die Bestimmung eines Entscheidungsbaumes (decission tree) dar. Es ist wenig bis gar nicht mathematisch. Deswegen habe ich es bestellt, denn ich will es als Basis nutzen für ein Buch, welches ich am schreiben bin und in dem es um Anwendung geht auch für Personen, die keine Mathematiker/Statistiker sind. Ich brauche jetzt das Rad nicht nochmal erfinden bei den decission trees. Der günstige Preis tat sein übriges.

El libro cumple con el propósito que es introducirte a los árboles de decisiones y al random forest.Me gustó que el enfoque es muy sencillo, práctico y directo. Las explicaciones son muy claras así cómo las ilustraciones.Por ahí la parte de random forest no me gustó tanto porque realmente la pusieron muy escueta pero se entiende por el espacio y porque el objetivo es una introducción para indagar más en otras fuentes.

Um bom livro para iniciantes entenderem o que são decision trees. Livro bem ilustrado, com exemplos simples e didática excelente.

I knew almost anything about decisions trees. I only had the math skills behind it but nothing about what a tree is and so on. I found this book interesting and perfectly suited for beginners like me.