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Machine Learning: Theoretical Foundations and Practical Applications [Paperback]

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  • Category: Books (Technology & Engineering)
  • ISBN-10:  981336520X
  • ISBN-10:  981336520X
  • ISBN-13:  9789813365209
  • ISBN-13:  9789813365209
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2022
  • Pub Date:  01-Mar-2022
  • SKU:  981336520X-11-SPRI
  • SKU:  981336520X-11-SPRI
  • Pages:  172
  • Pages:  172
  • Item ID: 104800920
  • List Price: $179.99
  • Seller: ShopSpell
  • Ships in: 5 business days
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  • Delivery by: Oct 16 to Oct 18
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 912 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms. 

Chapter 1. What do RDMs capture in Brain Responses and Computational Models?.- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems.- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification.- Chapter 4. Applications of Machine learning in industry 4.0.- Chapter 5. Web Semantics and Knowledge Graph.- Chapter 6. Machine Learning based Wireless Sensor Networks.- Chapter 7. AI to Machine Learning:lifeless automation and Issues.- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy.- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.

Dr. Siddharth Swarup Rautary presently working as Associate Professor at the School of Computer Engineering, Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India. He has teaching and research experience of more than 9 years. He did his doctoral degree from Indian Institute of Information Technoll3a

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