Alexia Audevart - Machine Learning Using TensorFlow Cookbook: Over 60 recipes on machine learning using deep learning solutions from Kaggle Masters and Google Developer Experts

Machine Learning Using TensorFlow Cookbook

Over 60 recipes on machine learning using deep learning solutions from Kaggle Masters and Google Developer Experts

Alexia Audevart

Konrad Banachewicz

Luca Massaron

BIRMINGHAM - MUMBAI

Machine Learning Using TensorFlow Cookbook

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Alexia Audevart, "Data & Enthusiasm," is a Google Developer Expert (GDE) in machine learning and the founder of datactik.

She is a data scientist and helps her clients solve business problems by making their applications smarter. Her goal is to create insights from data.

As a trainer and speaker, she works with professionals as well as universities and has even done her own TEDx talk.

Her first book is a collaboration on Artificial Intelligence and Neuroscience.

Thanks first to Max and Maxime, who took time out of their busy lives to review my chapters with such care.

I am also grateful to all the data enthusiasts I have met throughout my life, from whom I have learned a lot. Special thanks to our GDE coordinators, Paige Bailey, Jozef Vodicka, Justyna Politanska-Pyszko, and Soonson Kwon.

Many thanks to Tho, Lane, Lucas, Josphine, Mlissa, Bastein, and my wonderful extended family.

Last but not least, special thanks go to my parents, Guy and Christine, and my brother, Ludovic; your support has meant more than you will ever know.

Konrad Banachewicz holds a PhD in statistics from Vrije Universiteit Amsterdam. During his period in academia, he focused on problems of extreme dependency modeling in credit risk. In addition to his research activities, Konrad was a tutor, supervising Masters-level students. Starting with classical statistics, he slowly moved toward data mining and machine learning before the terms "data science" and "big data" became ubiquitous.

In the decade since his PhD, Konrad has worked in a variety of financial institutions on a wide array of quantitative data analysis problems. In the process, he became an expert on the entire lifetime of a data product cycle: from translating business requirements ("what do they really need?"), through data acquisition ("spreadsheets and flat files? really?"), wrangling, modeling and testing (the actually fun part), all the way to presenting the results to people allergic to mathematical terminology (which is the majority of business). He has covered different ends of the frequency spectrum in finance (from high-frequency trading to credit risk, and everything in between), predicted potato prices, and analyzed anomalies in the performance of large-scale industrial equipment.

As a person who himself has stood on the shoulders of giants, Konrad believes in sharing knowledge with others: it is very important to know how to approach practical problems with data science methods, but equally important to know how not to do it.

Konrad seems addicted to data analysis, so in his spare time he competes on Kaggle ("the home of data science").

I would like to thank my wife her patience (in listening to me talk about experience replay) and support (I run on tea the same way cars need gasoline) were invaluable. Thank you, honey.

Luca Massaron is a data scientist with more than a decade of experience in transforming data into smarter artifacts, in solving real-world problems, and in generating value for businesses and stakeholders. He is the author of best-selling books on AI, machine learning, and algorithms. Luca is also a Kaggle Master who reached no. 7 in the worldwide user rankings for his performance in data science competitions and a Google Developer Expert (GDE) in machine learning.

My warmest thanks go to my family, Yukiko and Amelia, for their support and loving patience.

I also want to thank our GDE coordinators, Paige Bailey, Jozef Vodicka, Justyna Politanska-Pyszko, and Soonson Kwon, and all the members of this fantastic community of experts created by Google.

Karthik Muthuswamy graduated from NTU Singapore with a doctorate in computer science, specifically in the field of computer vision. He has co-authored many journal and conference papers as well as submitted patent applications in the field of machine learning.

He works for SAP, in Germany, as a Senior Data Scientist, to research and develop enterprise applications that could leverage machine learning. He has also co-authored books and online courses on different topics of machine learning, and is a contributor to many open-source software projects. He teaches machine learning to the software development community with an aim of reducing the barriers of entry to learning about machine learning.