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Integrating Deep Learning Algorithms to Overcome Challenges in Big Data

Description: 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.

Price: 150 AUD

Location: Hillsdale, NSW

End Time: 2025-02-06T02:11:59.000Z

Shipping Cost: 24.78 AUD

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EAN: 9780367466633

UPC: 9780367466633

ISBN: 9780367466633

MPN: N/A

Book Title: Integrating Deep Learning Algorithms to Overcome C

Item Length: 23.4 cm

Number of Pages: 204 Pages

Language: English

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

Publisher: Taylor & Francis Ltd

Publication Year: 2021

Subject: Engineering & Technology, Computer Science, Mathematics

Item Height: 234 mm

Item Weight: 558 g

Type: Textbook

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

Item Width: 156 mm

Format: Hardcover

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