Cart
Free US shipping over $10
Proud to be B-Corp

Advanced Data Science and Analytics with Python Jesus Rogel-Salazar (Imperial College London, UK)

Advanced Data Science and Analytics with Python By Jesus Rogel-Salazar (Imperial College London, UK)

Advanced Data Science and Analytics with Python by Jesus Rogel-Salazar (Imperial College London, UK)


Summary

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.

Advanced Data Science and Analytics with Python Summary

Advanced Data Science and Analytics with Python by Jesus Rogel-Salazar (Imperial College London, UK)

Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications.

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. Jesus 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.

About Jesus Rogel-Salazar (Imperial College London, UK)

Dr Jesus 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.

Table of Contents

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

Additional information

NPB9780429446610
9780429446610
0429446616
Advanced Data Science and Analytics with Python by Jesus Rogel-Salazar (Imperial College London, UK)
New
Hardback
Taylor & Francis Ltd
2020-05-05
424
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a new book - be the first to read this copy. With untouched pages and a perfect binding, your brand new copy is ready to be opened for the first time

Customer Reviews - Advanced Data Science and Analytics with Python