Advanced data science and analytics with python

By:

Rogel-Salazar, Jesus

Material type: Text

9781138315068

Subject(s):

DDC classification:

006.3 ROG-A

Contents:

1. Time Series 2. Speaking Naturally: Text and Natural Language Processing 3. Getting 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

Summary: "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 from the topics discuss 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. 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 in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app"--

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode	Item holds
Books	IIITD General Stacks	Computer Science and Engineering	006.3 ROG-A (Browse shelf(Opens below))	Available	Gifted by IIITD-IIC		G02597

Total holds: 0

Includes bibliographical references and index.

1. Time Series
2. Speaking Naturally: Text and Natural Language Processing 3. Getting 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

"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 from the topics discuss 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. 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 in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app"--

There are no comments on this title.

to post a comment.