Deep Learning: Convergence to Big Data Analytics
Language: English
Published by Springer, Springer Jan 2019, 2019
Series: Book 284 of 322 - SpringerBriefs in Computer Science
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 65.56
Quantity: 1 available
Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -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 to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning.Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues.The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 96 pp. Englisch.…
Seller Inventory # 9789811334580
- Title
- Deep Learning: Convergence to Big Data Analytics
- Author
- Murad Khan
- Publisher
- Springer, Springer Jan 2019
- Publication year
- 2019
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 9811334587
- ISBN 13
- 9789811334580
- Item weight
- 180 grams
- Dimensions
- 235x155x6 mm
- Series
- Book 284 of 322: SpringerBriefs in Computer Science
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 to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning.
Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues.
The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.
"Synopsis" may belong to another edition of this title.
About the Author
Murad Khan received a B.S. degree in Computer Science from the University of Peshawar Pakistan in 2008. He completed his Ph.D. in Computer Science and Engineering at the School of Computer Science and Engineering at Kyungpook National University, Daegu, Korea. Dr. Khan has published over 50 international conference and journal papers along with two books chapters with Springer and CRC Press. He also served as a TPC member in reputable international conferences, such as ACM SAC 2017, ICFNDS 2017, and as a reviewer for numerous journals such as Future Generation Systems (Elsevier) and IEEE Access. In 2016, he received the Kyungpook National University’s Qualcomm Innovation Award for designing a smart home control system. He was also awarded the Bronze Medal at ACM SAC 2015, Salamanca, Spain, for his work on multi-criteria based handover techniques. He is a member of various communities, including ACM and IEEE, and CRC Press. His areas of expertise include ad-hoc and wireless networks, architecture design for Internet of Things, and communication protocol design for smart cities and homes, big data analytics, etc.
Bilal Jan received his M.S. and Ph.D. degrees from the Department of Control and Computer Engineering (DAUIN) Politecnico di Torino, Italy, in 2010 and 2015 respectively. He has published several papers in reputed journals and conferences. He is currently working as Assistant Professor and Head of the Department of Computer Science, FATA University, Darra Adam Khel, FR Kohat, Pakistan. He is a reviewer for numerous leading journals. His research interests include general purpose programming in GPUs, high-performance computing, wireless sensor networks, Internet of things (IoT), deep learning and big data.
Haleem Farman received his M.S. degree from the International Islamic University, Islamabad, Pakistan in 2008. He is currently pursuing his Ph.D. degree in Computer Science at the Department of Computer Science, University of Peshawar,Pakistan, and working as a lecturer at the Department of Computer Science, Islamia College Peshawar, Pakistan. He has authored/co-authored more than 20 research papers in respected journals and conferences. In addition, he serves as an invited reviewer for several journals, such as Elsevier Sustainable Cities and Society. His fields of interest include wireless sensor networks, Internet of Things, big data analytics, privacy, optimization techniques and quality of service issues in wireless networks.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
Shipping rates from Germany to U.S.A.
| Item | 60 to 60 business days | 60 to 60 business days |
|---|---|---|
| First item | £ 50.99 | £ 63.74 |
Payment methods
- Check
- Paypal
Store description
Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur
Specialty
Modernes Antiquariat - Bücher von 1960 bis heuteSeller's business information
buchversandmimpf2000
Germany
Terms of sale
Impressum
Gesetzliche Anbieterkennung:
Thorsten Retsch
Buchversand Mimpf2000
Oberölschnitz 16
95517 Emtmannsberg
Deutschland
Telefon: 092092023188
E-Mail: order@buchversandmimpf2000.de
USt-IdNr.: DE 235096871
Alternative Streitbeilegung:
Die Europäische Kommission stellt eine Plattform für die außergerichtliche Online-Streitbeilegung (OS-Plattform) bereit, aufrufbar unter http://ec.europa.eu/odr.
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to buchversandmimpf2000, Emtmannsberg, BAYE, Germany, +49 09209-2023188, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
Soweit in der Artikelbeschreibung keine andere Frist angegeben ist, erfolgt die Lieferung der Ware innerhalb von 3-5 Werktagen nach Vertragsschluss, bei Vorauszahlung erst nach Eingang des vollständigen Kaufpreises und der Versandkosten. Alle Preise inkl. MwSt.