Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics [Paperback]

Data science revolves around two giants, which are 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 along with deep learning systems.

1. A Study on Big Data and Arti
cial Intelligence Techniques in Agricultural Sector 2. Deep Learning Models for Object Detection in Self-Driven Cars 3. Deep Learning for Analyzing the Data on Object Detection and Recognition 4. Emerging Applications of Deep Learning 5. Emerging Trend and Research Issues in Deep Learning with Cloud Computing 6. An Investigation of Deep Learning 7. A Study and Comparative Analysis of Various Use Cases of NLP Using Sequential Transfer Learning Techniques 8. Deep Learning for Medical Dataset Classi
cation Based on Convolutional Neural Networks 9. Deep Learning in Medical Image Classi
cation 10 A Comparative Review of the Role of Deep Learning in Medical Image Processing

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.

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