Название: Nature-Inspired Algorithms for Big Data Frameworks Автор: Hema Banati, Shikha Mehta
Издательство: IGI Global
Серия: Advances in Computational Intelligence and Robotics
Год: 2018
Страниц: 436
Язык: английский
Формат: pdf (true)
Размер: 18.6 MB
Traditional approaches like artificial neural networks, in spite of their intelligent support such as learning from large amount of data, are not useful for big data analytics for many reasons. The book discusses the difficulties while analyzing big data and introduces deep learning as a solution. The chapter 1 discusses various deep learning techniques and models for big data analytics. The chapter presents necessary fundamentals of an artificial neural network, deep learning, and big data analytics. Different deep models such as autoencoders, deep belief nets, convolutional neural networks, recurrent neural networks, reinforcement learning neural networks, multi model approach, parallelization, and cognitive computing are discussed here, with the latest research and applications.
