Features:
Targets readers with a background in programming, who are interested in the tools used in data analytics and data science
Uses Python throughout
Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs
Focuses on the practical use of the tools rather than on lengthy explanations
Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path
The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book.
Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences ? in this case, literally to the users? fingertips in the form of an iPhone app.
About the Author
Dr. Jes?s Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.
