Integrating deep learning algorithms to overcome challenges in big data analytics:
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 Le...
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| Other Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boca Raton ; London ; New York
CRC Press, Taylor & Francis Group
2022
|
| Edition: | First edition |
| Series: | Green engineering and technology: Concepts and applications
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| Subjects: | |
| Summary: | 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. FEATURESProvides insight into the skill set that leverages one’s strength to act as a good data analystDiscusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-makingCovers numerous potential applications in healthcare, education, communication, media, and entertainmentOffers innovative platforms for integrating Big Data and Deep LearningPresents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big DataThis book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts |
| Item Description: | 1. Deep Learning for Analyzing the Big Data on Gaming Sector. 2. Deep Learning for Text Analysis. 3. Deep Learning for Analyzing the Data on Humanoid Robots. 4. Deep Learning for Analyzing the Data in IoT Based System. 5. Deep Learning for Analyzing the Data on Object Detection and Recognition. 6. Deep Learning for Medical Dataset Classification. 7. Performance Evaluation and Deep Learning Optimization. 8. Deep Learning for Image Data Classification. 9. World Wide Web Analysis. 10. Cyber Physical System Analysis. 11. Big Data Analysis for Financial Sector (Banking, Insurance, Stock Exchange etc.). 12. Learning Algorithm for Smart Cities using Big Data. 13. Big Data Analytics in Engineering. 14. Big Data Analytics in Healthcare. 15. Learning Algorithm for Social Media Data Analytics. 16. Big Data Analytics in Agriculture. 17. Big Data Analytics for Cloud, Mist and Fog Prediction. 18. Innovative Large-Scale Models for Deep Learning Algorithms and Architectures. 19. Innovative Platforms for Integrating Big Data and Deep Learning |
| Physical Description: | xii, 204 Seiten Illustrationen, Diagramme 558 grams |
| ISBN: | 9780367466633 9781032104461 |
Staff View
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| isbn | 9780367466633 9781032104461 |
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| physical | xii, 204 Seiten Illustrationen, Diagramme 558 grams |
| publishDate | 2022 |
| publishDateSearch | 2022 |
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| publisher | CRC Press, Taylor & Francis Group |
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| spelling | Integrating deep learning algorithms to overcome challenges in big data analytics edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan First edition Boca Raton ; London ; New York CRC Press, Taylor & Francis Group 2022 xii, 204 Seiten Illustrationen, Diagramme 558 grams txt rdacontent n rdamedia nc rdacarrier Green engineering and technology: Concepts and applications 1. Deep Learning for Analyzing the Big Data on Gaming Sector. 2. Deep Learning for Text Analysis. 3. Deep Learning for Analyzing the Data on Humanoid Robots. 4. Deep Learning for Analyzing the Data in IoT Based System. 5. Deep Learning for Analyzing the Data on Object Detection and Recognition. 6. Deep Learning for Medical Dataset Classification. 7. Performance Evaluation and Deep Learning Optimization. 8. Deep Learning for Image Data Classification. 9. World Wide Web Analysis. 10. Cyber Physical System Analysis. 11. Big Data Analysis for Financial Sector (Banking, Insurance, Stock Exchange etc.). 12. Learning Algorithm for Smart Cities using Big Data. 13. Big Data Analytics in Engineering. 14. Big Data Analytics in Healthcare. 15. Learning Algorithm for Social Media Data Analytics. 16. Big Data Analytics in Agriculture. 17. Big Data Analytics for Cloud, Mist and Fog Prediction. 18. Innovative Large-Scale Models for Deep Learning Algorithms and Architectures. 19. Innovative Platforms for Integrating Big Data and Deep Learning 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. FEATURESProvides insight into the skill set that leverages one’s strength to act as a good data analystDiscusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-makingCovers numerous potential applications in healthcare, education, communication, media, and entertainmentOffers innovative platforms for integrating Big Data and Deep LearningPresents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big DataThis book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts bisacsh / COMPUTERS / Database Management / Data Mining bisacsh / COMPUTERS / Intelligence (AI) & Semantics Sujatha, R. edt Aarthy, S. L. edt Vettriselvan, R. edt Erscheint auch als Online-Ausgabe 978-1-00303845-0 |
| spellingShingle | Integrating deep learning algorithms to overcome challenges in big data analytics bisacsh / COMPUTERS / Database Management / Data Mining bisacsh / COMPUTERS / Intelligence (AI) & Semantics |
| title | Integrating deep learning algorithms to overcome challenges in big data analytics |
| title_auth | Integrating deep learning algorithms to overcome challenges in big data analytics |
| title_exact_search | Integrating deep learning algorithms to overcome challenges in big data analytics |
| title_full | Integrating deep learning algorithms to overcome challenges in big data analytics edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan |
| title_fullStr | Integrating deep learning algorithms to overcome challenges in big data analytics edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan |
| title_full_unstemmed | Integrating deep learning algorithms to overcome challenges in big data analytics edited by R. Sujatha, S.L. Aarthy, and R. Vettriselvan |
| title_short | Integrating deep learning algorithms to overcome challenges in big data analytics |
| title_sort | integrating deep learning algorithms to overcome challenges in big data analytics |
| topic | bisacsh / COMPUTERS / Database Management / Data Mining bisacsh / COMPUTERS / Intelligence (AI) & Semantics |
| topic_facet | bisacsh / COMPUTERS / Database Management / Data Mining bisacsh / COMPUTERS / Intelligence (AI) & Semantics |
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