Download the fantastic book titled Handbook of Deep Learning Applications written by Valentina Emilia Balas, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Handbook of Deep Learning Applications", which was released on 25 February 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.
Summary of Handbook of Deep Learning Applications by Valentina Emilia Balas PDF
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
Detail About Handbook of Deep Learning Applications PDF
- Author : Valentina Emilia Balas
- Publisher : Springer
- Genre : Technology & Engineering
- Total Pages : 383 pages
- ISBN : 3030114791
- Release Date : 25 February 2019
- PDF File Size : 21,8 Mb
- Language : English
- Rating : 4/5 from 21 reviews
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