FREE delivery to all EXCLUSIVE BOOKS stores nationwide. FREE delivery to your door on all orders over R450. Excludes all international deliveries.

  • Safe delivery by Christmas SANTA SAFE
    Deep Learning for Data Analytics

Deep Learning for Data Analytics

Himansu Das
    Product form
      FORMAT:

      R 5,002.00 Price and availability exclusive to website

      YOU COULD EARN 5,002 FUTURE RETAIL DISCOUNTS.
      ESTIMATED DELIVERY: Approx. 20 - 30 Business Days
      BUY NOW PAY LATER
      From R 833.66 per month!
      3x monthly payments of R 1,667.33 with
      4x fortnightly payments of R 1,250.50 with
      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.
      Format: CONTRIBUTORS: Himansu Das EAN: 9780128197646 COUNTRY: United States PAGES: WEIGHT: 450 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science Publishing Co Inc DATE PUBLISHED: 2020-05-31 CITY: GENRE: SCIENCE / Biotechnology, TECHNOLOGY & ENGINEERING / Biomedical WIDTH: 191 cm SPINE:

      Book Themes:

      Biomedical engineering, Biotechnology

      Customer Reviews

      Be the first to write a review
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      Himansu Das is working as an as Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He has received his B. Tech and M. Tech degree from Biju Pattnaik University of Technology (BPUT), Odisha, India. He has published several research papers in various international journals and conferences. He has also edited several books of international repute. He is associated with different international bodies as Editorial/Reviewer board member of various journals and conferences. He is a proficient in the field of Computer Science Engineering and served as an organizing chair, publicity chair and act as member of program committees of many national and international conferences. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc., His research interest includes Grid Computing, Cloud Computing, and Machine Learning. He has also 10 years of teaching and research experience in different engineering colleges. Chittaranjan Pradhan is working at School of Computer Engineering, KIIT University, India. He obtained his Bachelors, Masters and PhD degree in Computer Science & Engineering stream. His research are includes Information Security, Image Processing, Data Analytics and Multimedia Systems. Dr. Pradhan has published more than 40 articles in the national and international journals and conferences. Also, he has been associated to a number of events organized at national and international level. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc. He has also experience of more than 10 years in teaching and research activities. Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK, and also holds the position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held the honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He got his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer Nature), Data-Intensive Research (Springer Nature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He is an associate editor of IET Image Processing (Wiley) and an editorial board member of Complex & Intelligent Systems (Springer Nature), Applied Soft Computing (Elsevier), and more. He has written 110 books and over 300 other publications in the areas of medical imaging, machine learning, computer aided diagnosis, data mining, etc. His works have been cited over 15,000 times. He is India’s Ambassador to the International Federation for Information Processing—Young ICT Group and a s
      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.
      Format: CONTRIBUTORS: Himansu Das EAN: 9780128197646 COUNTRY: United States PAGES: WEIGHT: 450 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science Publishing Co Inc DATE PUBLISHED: 2020-05-31 CITY: GENRE: SCIENCE / Biotechnology, TECHNOLOGY & ENGINEERING / Biomedical WIDTH: 191 cm SPINE:

      Book Themes:

      Biomedical engineering, Biotechnology

      Customer Reviews

      Be the first to write a review
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      Himansu Das is working as an as Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He has received his B. Tech and M. Tech degree from Biju Pattnaik University of Technology (BPUT), Odisha, India. He has published several research papers in various international journals and conferences. He has also edited several books of international repute. He is associated with different international bodies as Editorial/Reviewer board member of various journals and conferences. He is a proficient in the field of Computer Science Engineering and served as an organizing chair, publicity chair and act as member of program committees of many national and international conferences. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc., His research interest includes Grid Computing, Cloud Computing, and Machine Learning. He has also 10 years of teaching and research experience in different engineering colleges. Chittaranjan Pradhan is working at School of Computer Engineering, KIIT University, India. He obtained his Bachelors, Masters and PhD degree in Computer Science & Engineering stream. His research are includes Information Security, Image Processing, Data Analytics and Multimedia Systems. Dr. Pradhan has published more than 40 articles in the national and international journals and conferences. Also, he has been associated to a number of events organized at national and international level. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc. He has also experience of more than 10 years in teaching and research activities. Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK, and also holds the position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held the honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He got his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer Nature), Data-Intensive Research (Springer Nature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He is an associate editor of IET Image Processing (Wiley) and an editorial board member of Complex & Intelligent Systems (Springer Nature), Applied Soft Computing (Elsevier), and more. He has written 110 books and over 300 other publications in the areas of medical imaging, machine learning, computer aided diagnosis, data mining, etc. His works have been cited over 15,000 times. He is India’s Ambassador to the International Federation for Information Processing—Young ICT Group and a s

      Recently viewed products

      Login

      Forgot your password?

      Don't have an account yet?
      Create account