Coelho Luis Pedro - Building Machine Learning Systems with Python

Luis Pedro Coelho is a computational biologist: someone who uses computers as a tool to understand biological systems. In particular, Luis analyzes DNA from microbial communities to characterize their behavior. Luis has also worked extensively in bioimage informaticsthe application of machine learning techniques for the analysis of images of biological specimens. His main focus is on the processing and integration of large-scale datasets.

Luis has a PhD from Carnegie Mellon University, one of the leading universities in the world in the area of machine learning. He is the author of several scientific publications.

Luis started developing open source software in 1998 as a way to apply real code to what he was learning in his computer science courses at the Technical University of Lisbon. In 2004, he started developing in Python and has contributed to several open source libraries in this language. He is the lead developer on the popular computer vision package for Python and mahotas, as well as the contributor of several machine learning codes.

Luis currently divides his time between Luxembourg and Heidelberg.

I thank my wife, Rita, for all her love and support and my daughter, Anna, for being the best thing ever.

Willi Richert has a PhD in machine learning/robotics, where he used reinforcement learning, hidden Markov models, and Bayesian networks to let heterogeneous robots learn by imitation. Currently, he works for Microsoft in the Core Relevance Team of Bing, where he is involved in a variety of ML areas such as active learning, statistical machine translation, and growing decision trees.

This book would not have been possible without the support of my wife, Natalie, and my sons, Linus and Moritz. I am especially grateful for the many fruitful discussions with my current or previous managers, Andreas Bode, Clemens Marschner, Hongyan Zhou, and Eric Crestan, as well as my colleagues and friends, Tomasz Marciniak, Cristian Eigel, Oliver Niehoerster, and Philipp Adelt. The interesting ideas are most likely from them; the bugs belong to me.

Matthieu Brucher holds an engineering degree from the Ecole Suprieure d'Electricit (Information, Signals, Measures), France and has a PhD in unsupervised manifold learning from the Universit de Strasbourg, France. He currently holds an HPC software developer position in an oil company and is working on the next generation reservoir simulation.

Maurice HT Ling has been programming in Python since 2003. Having completed his PhD in Bioinformatics and BSc (Hons.) in Molecular and Cell Biology from The University of Melbourne, he is currently a Research Fellow at Nanyang Technological University, Singapore, and an Honorary Fellow at The University of Melbourne, Australia. Maurice is the Chief Editor for Computational and Mathematical Biology , and co-editor for The Python Papers . Recently, Maurice cofounded the first synthetic biology start-up in Singapore, AdvanceSyn Pte. Ltd., as the Director and Chief Technology Officer. His research interests lies in lifebiological life, artificial life, and artificial intelligenceusing computer science and statistics as tools to understand life and its numerous aspects. In his free time, Maurice likes to read, enjoy a cup of coffee, write his personal journal, or philosophize on various aspects of life. His website and LinkedIn profile are http://maurice.vodien.com and http://www.linkedin.com/in/mauriceling, respectively.

Radim ehek is a tech geek and developer at heart. He founded and led the research department at Seznam.cz, a major search engine company in central Europe. After finishing his PhD, he decided to move on and spread the machine learning love, starting his own privately owned R&D company, RaRe Consulting Ltd. RaRe specializes in made-to-measure data mining solutions, delivering cutting-edge systems for clients ranging from large multinationals to nascent start-ups.

Radim is also the author of a number of popular open source projects, including gensim and smart_open.

A big fan of experiencing different cultures, Radim has lived around the globe with his wife for the past decade, with his next steps leading to South Korea. No matter where he stays, Radim and his team always try to evangelize data-driven solutions and help companies worldwide make the most of their machine learning opportunities.

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