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Machine Learning. A Practical Approach on the Statistical...

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Machine Learning. A Practical Approach...

Machine Learning. A Practical Approach on the Statistical Learning Theory

Rodrigo Fernandes de Mello, Moacir Antonelli Ponti

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سب زمرہ:

سال:

2018

ناشر کتب:

Springer

زبان:

english

صفحات:

368

ISBN 10:

3319949896

ISBN 13:

9783319949895

فائل:

PDF, 11.18 MB

IPFS:

,

english, 2018

کاپی رائٹ ہولڈر کی شکایت کی وجہ سے یہ کتاب ڈاؤن لوڈ کے لیے دستیاب نہیں ہے۔

Beware of he who would deny you access to information, for in his heart he dreams himself your master

— Pravin Lal

آپ کو دلچسپی ہوسکتی ہے

D. Michie, D. J. Spiegelhalter, C. C. Taylor — Machine Learning, Neural and Statistical Classification

Sanjeev Kulkarni, Gilbert Harman — An Elementary Introduction to Statistical Learning Theory

Sumio Watanabe — Algebraic Geometry and Statistical Learning Theory

Vladimir Vapnik — The Nature Of Statistical Learning

Olivier Chapelle, Bernhard SchÃ¶lkopf, Alexander Zien — Semi-Supervised Learning

Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang — A Comprehensive Guide to Machine Learning

GRSSB — Support Vector Machines (ML)

Pooja Saigal — Support Vector Machines

Max Welling — A First Encounter with Machine Learning

AlexJ.SmolaandVishyS.V.N.Vishwanathan — AnIntroductiontoMachineLearning

— Лекции по нейроинформатике 2007. Часть 1

Abu-Mostafa Y.S., Magdon-Ismail M., Lin H — Supplementary materials for Learning from data

Suykens J. — A short Introduction to Support Vector Machines and Kernelbased Learning

Antoine Bordes — New Algorithms for Large-Scale Support Vector Machines

Roberto Basili, Alessandro Moschitti — Automatic Text Categorization: from Information Retrieval to Support Vector Learning

Gökhan H. Bakir, Thomas Hofmann, Bernhard SchÃ¶lkopf, Alexander J. Smola, Ben Taskar, S. V. N. Vishwanathan — Predicting Structured Data

Léon Bottou, Olivier Chapelle, Dennis DeCoste, Jason Weston — Large-Scale Kernel Machines

Smola A.J., et al. (eds.) — Advances in large margin classifiers

Lutz H. Hamel — Knowledge Discovery with Support Vector Machines (Wiley Series on Methods and Applications in Data Mining)

Nello Cristianini, John Shawe-Taylor — An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Anil Ananthaswamy — Why Machines Learn: The Elegant Math Behind Modern AI

Anil Ananthaswamy — Why Machines Learn: The Elegant Math Behind Modern AI

Jianxin Wu — Essentials of Pattern Recognition: An Accessible Approach

Kolla Bhanu Prakash — Machine Learning for Industrial Applications

Naiyang Deng; Yingjie Tian; Chunhua Zhang — Support vector machines : optimization based theory, algorithms, and extensions

Naiyang Deng — Support Vector Machines

Christos Christodoulou, Manel Martinez Ramon — Support Vector Machines for Antenna Array Processing and Electromagnetics

Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin — Learning from Data

Michael Biehl — The Shallow and the Deep: A biased introduction to neural networks and old school machine learning

Andreas Wichert, Luis Sa-Couto — Machine Learning - A Journey To Deep Learning: With Exercises And Answers

Yong Shi — Advances in Big Data Analytics: Theory, Algorithms and Practices

Ye, Jong Chul — Geometry of Deep Learning: A Signal Processing Perspective

Johan A K Suykens, Tony Van Gestel, Jos De Brabanter, Bart De Moor, Joos Vandewalle — Least squares support vector machines

Amita Pal, Sankar K Pal — Pattern Recognition and Big Data

Hang Li — Machine Learning Methods

اہم جملے