Jesus Rogel-Salazar

Advanced Data Science and Analytics with Python (eBook, ePUB)

• Format: ePub

Produktbeschreibung

The book is intended for practitioners in data science and data analytics in both academic and business environments. It aims to present the reader with concepts in data science and analytics that were deemed to be more advanced or simply out of scope in the author's first book.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 420
• Erscheinungstermin: 5. Mai 2020
• Englisch
• ISBN-13: 9780429822315
• Artikelnr.: 59387348

Autorenporträt

Dr Jesús Rogel-Salazar is a lead data scientist with experience in the field working for companies such as AKQA, IBM Data Science Studio, Dow Jones, Barclays and Tympa Health Technologies. 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. He obtained his doctorate in Physics at Imperial College London for work on quantum atom optics and ultra-cold matter.

He has held a position as senior lecturer in mathematics as well as a consultant and data scientist for a number of years in a variety of industries including science, finance, marketing, people analytics and health, among others. He is the author of Data Science and Analytics with Python and Essential Matlab and Octave, both also published with CRC Press. His interests include mathematical modelling, data science and optimisation in a wide range of applications including optics, quantum mechanics, data journalism, finance and health.

Inhaltsangabe

1. No Time To Lose: Time Series Analysis
2. Speaking Naturally: Text and Natural Language Processing
3. Let Us Get Social: Graph Theory and Social Network Analysis
4. Thinking Deeply: Neural Networks and Deep Learning
5. Here Is One I Made Earlier: Machine Learning Deployment

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1. No Time To Lose: Time Series Analysis

2. Speaking Naturally: Text and Natural Language Processing

3. Let Us Get Social: Graph Theory and Social Network Analysis

4. Thinking Deeply: Neural Networks and Deep Learning

5. Here Is One I Made Earlier: Machine Learning Deployment