Description
Taylor & Francis Advanced Data Science And Analytics With Python by Jesus Rogel-Salazar
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._x000D__x000D__x000D_Features:_x000D__x000D__x000D__x000D__x000D_Targets readers with a background in programming, who are interested in the tools used in data analytics and data science_x000D_Uses Python throughout_x000D_Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs_x000D_Focuses on the practical use of the tools rather than on lengthy explanations_x000D_Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path_x000D__x000D__x000D_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._x000D__x000D__x000D_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._x000D__x000D__x000D_About the Author_x000D__x000D__x000D_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._x000D_ _x000D_
1. No Time To Lose: Time Series Analysis_x000D_
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2. Speaking Naturally: Text and Natural Language Processing_x000D_
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3. Let Us Get Social: Graph Theory and Social Network Analysis_x000D_
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4. Thinking Deeply: Neural Networks and Deep Learning_x000D_
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5. Here Is One I Made Earlier: Machine Learning Deployment_x000D_