MEET THE AUTHOR
Oliver Theobald works as a Senior Operations Specialist for Alibaba Cloud where he works with cloud architects, machine learning engineers and product managers to produce content for customers regarding AI and cloud-based solutions in big data, smart cities, and security. He is also a part-time Instructor for Tutsplus.com.
Oliver is a graduate of the Royal Melbourne Institute of Technology and is an Australian national of British and Austrian descent. Oliver has been living in Asia since 2011. He currently works in both Hangzhou and Beijing, China.
Oliver writes regular technical content on the topics of cloud computing, ICP registration, artificial intelligence, e-commerce, and machine learning. His programming language of choice is Python and in his free time he enjoys studying Chinese, selecting his Fantasy Premier League team each week (in the process of developing a quantitative model to predict a players future financial value), and listening to historical fiction and non-fiction audiobooks.
Machine Learning for Absolute Beginners has been written and designed for absolute beginners. This means plain-English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home.
This title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing specific algorithms applied in machine learning, including their pros and cons. At the end of the book, I share insights and advice on further learning and careers in this space.
Did exactly what it claimed to do, provide a high-level, easily accessible intro/scan of the subject. Nice section on getting into the field as well.
As a beginner I felt the pace of the book was very manageable and each concept is well explained with clear points, often backed up with visual illustrations. You get a good context on what is ML, the algorithms that power ML, and guidance on further learning careers. This book is not a substitute for a textbook but would be a nice complementary resource for anyone starting out in this subject. I feel that business folks or journalists who don’t have a lot of time to sit down and learn this advanced field and who need a rapid snapshot of ML would do well to read this book. As a title geared to ‘absolute beginners’, I would not recommend to more advanced stage learners to read this book. For me though it hit the spot. Would look forward to a second title in this series if there is one.