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 international customers regarding AI and cloud-based solutions in big data, smart cities, and security. He is also a part-time Instructor for

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 (in the process of developing a quantitative model to predict a players’ future financial value), and listening to historical fiction and non-fiction audiobooks.


Recommender systems are perhaps the most visible application of machine learning and data mining today and their uncanny ability to convert our unspoken actions into items we desire is both addicting and concerning.

These data-driven systems are eroding the dominance of traditional search while aiding the discoverability of items that might not otherwise have been found. Recommender systems are here to stay and for anyone beginning their journey in data science, it stands as a lucrative space for future employment.

This book is designed for beginners with basic background knowledge of data science, including classical statistics and computing programming. If this is your first exposure to data science, you may want to spend a few hours to read my first book Machine Learning for Absolute Beginners before you get started here.


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