Deep Learning for Data Analytics Book [PDF] Download

Download the fantastic book titled Deep Learning for Data Analytics written by Himansu Das, 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 "Deep Learning for Data Analytics", which was released on 29 May 2020. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Science genre.

Summary of Deep Learning for Data Analytics by Himansu Das PDF

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis. Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications. Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including Deep Learning networks, deep feature learning, deep learning toolboxes, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networks Provides readers with an introduction to Deep Learning, along with coverage of deep belief networks, convolutional neural networks, Restricted Boltzmann Machines, data analytics basics, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning


Detail About Deep Learning for Data Analytics PDF

  • Author : Himansu Das
  • Publisher : Academic Press
  • Genre : Science
  • Total Pages : 220 pages
  • ISBN : 0128226080
  • PDF File Size : 47,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Deep Learning for Data Analytics

Deep Learning for Data Analytics
  • Publisher : Academic Press
  • File Size : 34,6 Mb
  • Release Date : 29 May 2020
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Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical

Deep Learning in Data Analytics

Deep Learning in Data Analytics
  • Publisher : Springer Nature
  • File Size : 26,8 Mb
  • Release Date : 11 August 2021
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This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning

Deep Learning: Convergence to Big Data Analytics

Deep Learning: Convergence to Big Data Analytics
  • Publisher : Springer
  • File Size : 30,5 Mb
  • Release Date : 30 December 2018
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This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used

Advanced Deep Learning Applications in Big Data Analytics

Advanced Deep Learning Applications in Big Data Analytics
  • Publisher : IGI Global
  • File Size : 21,6 Mb
  • Release Date : 16 October 2020
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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

Advanced Data Analytics Using Python

Advanced Data Analytics Using Python
  • Publisher : Apress
  • File Size : 33,6 Mb
  • Release Date : 29 March 2018
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Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL

Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python
  • Publisher : Academic Press
  • File Size : 37,9 Mb
  • Release Date : 05 June 2020
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Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and