☆★☆Python Machine Learning Illustrated Guide For Beginners & Intermediates☆★☆ Machines Can Learn ?! Automation and systematization is taking over the world. Slowly but surely we continuously see the rapid expansion of artificial intelligence, self-check out cash registers, automated phone lines, people-less car-washes , etc. The world is changing, find out how python programming ties into machine learning so you don't miss out on this next big trend. This is your beginner's step by step guide with illustrated pictures! Let's face it, machine learning is here to stay for the foreseeable future and will impact the lives billions worldwide! Drastically changing the world we live in the most fundamental ways, from our perceptions, life-style, thinking and in other aspects as well. What You Will Learn.. Linear & Polynomial RegressionSupport Vector Machines Decision Trees Random Forest KNN Algorithm Naive Bayes Algorithm Unsupervised LearningClusteringCross ValidationGrid Search And, much, much more! If you want to learn more about python machine learning it is highly recommended you start from the ground up by using this book. Books on this subject matter normally retail for $100s of dollars! Why not start off by making a small and affordable investment with your illustrated beginners guide that walks you through python machine learning step by step. Why choose this book? Addresses Fundamental Concepts Goes Straight To The Point, No fluff or Nonsense Practical Examples High Quality Diagrams "Noob friendly" (Good For Beginners & Intermediates) Contains Various Aspects of Machine Learning Endorses Learn "By Doing Approach" Concise And To The Point As an added bonus, I give you my Data Analytics E- book completely FREE. You can find this gift inside the book. I been working tirelessly to provide you quality books at an affordable price. I believe this book will give you the confidence to tackle python machine learning at a fundamental level. What are you waiting for? Make the greatest investment in YOUR knowledge base right now.
Poorly written, littered with typographical mistakes including pagination errors and hyperlinks with just the word 'link'.
Content-wise, the book is less an introduction and more a set of predefined scripts that are repetitive and do little to teach the reader about machine learning. The book starts with a basic, albeit traditional, 'hello world' program and then swiftly moves on to reasonably complex machine learning with little in the way of explanation.
As for being illustrated, it isn't really. Bar a couple of graphs here and there the majority of what might be considered illustrations are simply code formatted to look as such.
Had I known this was self-published I would never have bought it, and I would advise you to look elsewhere.
I like this book because it explains (briefly) different approaches. It is a good starting point that might help to narrow your options (if you have doubts about a model that you want to use)