Deep Learning Applications And Challenges In Big Data Analytics


Download Deep Learning Applications And Challenges In Big Data Analytics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Learning Applications And Challenges In Big Data Analytics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

Advanced Deep Learning Applications in Big Data Analytics


Advanced Deep Learning Applications in Big Data Analytics

Author: Bouarara, Hadj Ahmed

language: en

Publisher: IGI Global

Release Date: 2020-10-16


DOWNLOAD





Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Handbook of Research on Machine and Deep Learning Applications for Cyber Security


Handbook of Research on Machine and Deep Learning Applications for Cyber Security

Author: Ganapathi, Padmavathi

language: en

Publisher: IGI Global

Release Date: 2019-07-26


DOWNLOAD





As the advancement of technology continues, cyber security continues to play a significant role in today’s world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.

Research Anthology on Big Data Analytics, Architectures, and Applications


Research Anthology on Big Data Analytics, Architectures, and Applications

Author: Management Association, Information Resources

language: en

Publisher: IGI Global

Release Date: 2021-09-24


DOWNLOAD





Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.