Use machine learning and data-based methods to build intelligent applications using Packt's new book and eBook

May 2014 | Open Source

Packt is pleased to announce the release of Learning scikit-learn: Machine Learning in Python, a fast-paced and concise guide that teaches programmers how to use Python and scikit-learn to create intelligent applications. This book is available now in popular DRM-free formats such as Amazon Kindle, e-pub, and PDF.

About the authors:
A computer engineer with experience in the theory and application of Artificial Intelligence (AI) specializing in machine learning and Natural Language Processing (NLP), Raúl Garreta has worked for 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; he acts 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 they have been catering to many clients in Silicon Valley.

Guillermo Moncecchi is a Natural Language Processing researcher at the Universidad de la República of Uruguay. He received a PhD in Informatics from the Universidad de la República, Uruguay, and a PhD in Language Sciences from the Université Paris Ouest, France. He has participated in several international projects on NLP. He has almost 15 years of teaching experience on the 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 area of Geographical Information Systems. He is one of the Montevideo Open Data movement leaders, promoting the publication and exploitation of the city's data.

Machine learning, the art of creating applications that learn from experience and data, has been around for many years. However, in the era of Big Data, huge amounts of information is being generated. This makes machine learning an unavoidable source of new data-based approximations for problem solving.

Learning scikit-learn: Machine Learning in Python starts with a brief introduction to the core concepts of machine learning with a simple example. Then, using real-world applications and advanced features, it delves into the various advanced machine learning techniques. Readers will also learn how to evaluate their results and apply advanced techniques for preprocessing data.

With this book, readers will learn how to use the Python programming language and the scikit-learn library to build applications that learn from experience, applying the main concepts and techniques of machine learning.

About Packt:
Packt is one of the most prolific and fastest-growing tech book publishers in the world. Originally focused on open source software, Packt books now focus on practicality, recognizing that readers are ultimately concerned with getting the job done. Packt’s digitally-focused business model allows them to publish up-to-date books in very specific areas.

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

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