Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics PDF

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics PDF

Name:
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics PDF

Published Date:
01/01/2022

Status:
[ Active ]

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Publisher:
CRC Press Books

Document status:
Active

Format:
Electronic (PDF)

Delivery time:
10 minutes

Delivery time (for Russian version):
200 business days

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$39.6
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ISBN: 9781000454536

Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems.

This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval.

FEATURES

Provides insight into the skill set that leverages one’s strength to act as a good data analyst

Discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-making

Covers numerous potential applications in healthcare, education, communication, media, and entertainment

Offers innovative platforms for integrating Big Data and Deep Learning

Presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big Data

This book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts.

Authors: R. Sujatha, S. L. Aarthy, R. Vettriselvan


Edition : 1
Number of Pages : 217
Published : 01/01/2022
isbn : 9781000454536

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