Guillermo Moncecchi - Learning scikit-learn machine learning in Python : experience the benefits of machine learning techniques by applying them to real-world problems using Python and the open source scikit-learn library

Ral Garreta is a Computer Engineer with much experience in the theory and application of Artificial Intelligence (AI), where he specialized in Machine Learning and Natural Language Processing (NLP).

He has an entrepreneur profile with much interest in the application of science, technology, and innovation to the Internet industry and startups. He has worked in many software companies, handling everything from video games to implantable medical devices.

In 2009, he co-founded Tryolabs with the objective to apply AI to the development of intelligent software products, where he performs as the CTO and Product Manager of the company. Besides the application of Machine Learning and NLP, Tryolabs' expertise lies in the Python programming language and has been catering to many clients in Silicon Valley. Raul has also worked in the development of the Python community in Uruguay, co-organizing local PyDay and PyCon conferences.

He is also an assistant professor at the Computer Science Institute of Universidad de la Repblica in Uruguay since 2007, where he has been working on the courses of Machine Learning, NLP, as well as Automata Theory and Formal Languages. Besides this, he is finishing his Masters degree in Machine Learning and NLP. He is also very interested in the research and application of Robotics, Quantum Computing, and Cognitive Modeling. Not only is he a technology enthusiast and science fiction lover (geek) but also a big fan of arts, such as cinema, photography, and painting.

I would like to thank my girlfriend for putting up with my long working sessions and always supporting me. Thanks to my parents, grandma, and aunt Pinky for their unconditional love and for always supporting my projects. Thanks to my friends and teammates at Tryolabs for always pushing me forward. Thanks Guillermo for joining me in writing this book. Thanks Diego Garat for introducing me to the amazing world of Machine Learning back in 2005.

Also, I would like to have a special mention to the open source Python and scikit-learn community for their dedication and professionalism in developing these beautiful tools.

Guillermo Moncecchi is a Natural Language Processing researcher at the Universidad de la Repblica of Uruguay. He received a PhD in Informatics from the Universidad de la Repblica, Uruguay and a Ph.D in Language Sciences from the Universit Paris Ouest, France. He has participated in several international projects on NLP. He has almost 15 years of teaching experience on Automata Theory, Natural Language Processing, and Machine Learning.

He also works as Head Developer at the Montevideo Council and has lead the development of several public services for the council, particularly in the Geographical Information Systems area. He is one of the Montevideo Open Data movement leaders, promoting the publication and exploitation of the city's data.

I would like to thank my wife and kids for putting up with my late night writing sessions, and my family, for being there. You are the best I have.

Thanks to Javier Couto for his invaluable advice. Thanks to Ral for inviting me to write this book. Thanks to all the people of the Natural Language Group and the Instituto de Computacin at the Universidad de la Repblica. I am proud of the great job we do every day building the uruguayan NLP and ML community.

Andreas Hjortgaard Danielsen holds a Master's degree in Computer Science from the University of Copenhagen, where he specialized in Machine Learning and Computer Vision. While writing his Master's thesis, he was an intern research student in the Lampert Group at the Institute of Science and Technology (IST), Austria in Vienna. The topic of his thesis was object localization using conditional random fields with special focus on efficient parameter learning. He now works as a software developer in the information services industry where he has used scikit-learn for topic classification of text documents. See more on his website at http://www.hjortgaard.net/.

Noel Dawe is a Ph.D. student in the field of Experimental High Energy Particle Physics at Simon Fraser University, Canada. As a member of the ATLAS collaboration, he has been a part of the search team for the Higgs boson using high energy proton-proton collisions at CERN's Large Hadron Collider (LHC) in Geneva, Switzerland. In his free time, he enjoys contributing to open source scientific software, including scikit-learn. He has developed a significant interest toward Machine learning, to the benefit of his research where he has employed many of the concepts and techniques introduced in this book to improve the identification of tau leptons in the ATLAS detector, and later to extract the small signature of the Higgs boson from the vast amount of LHC collision data. He continues to learn and apply new data analysis techniques, some seen as unconventional in his field, to solve the problems of increasing complexity and growing data sets.

Gavin Hackeling is a Developer and Creative Technologist based in New York City. He is a graduate from New York University in Interactive Telecommunications Program.