Spende 15. September, 2024 – 1. Oktober, 2024 Über Spenden

Supplementary materials for Learning from data

Main
Supplementary materials for Learning...

Supplementary materials for Learning from data

Abu-Mostafa Y.S., Magdon-Ismail M., Lin H

0 / 0

Wie gefällt Ihnen dieses Buch?

Wie ist die Qualität der Datei?

Herunterladen Sie das Buch, um Ihre Qualität zu bewerten

Wie ist die Qualität der heruntergeladenen Dateien?

Jahr:

2015

Auflage:

web draft

Sprache:

english

Seiten:

289

Datei:

PDF, 13.24 MB

IPFS:

,

english, 2015

Online lesen

Die Konvertierung in ist im Gange

Die Konvertierung in ist fehlgeschlagen

Es kann für Sie interessant sein

United States. National Aeronautics and Space Administration.; Mueller, George Edwin; Mueller, George Edwin; United States. National Aeronautics and Space Administration; Slotkin, Arthur L — Doing the impossible: George E. Mueller and the management of NASA's Human Spaceflight Program

Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin — Learning From Data. A short course

Ronald T. Kneusel — Practical Deep Learning: A Python-Based Introduction

Bernhard Schlkopf, Alexander J. Smola — Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)

Lipo Wang — Advances in Natural Computation

Diego Andina, Duc Truong Pham (Eds.) — Computational Intelligence

it-ebooks — A Comprehensive Guide to Machine Learning (UCB CS189)

Desconocido — Hui Jiang Machine Learning Fundamentals A Concise Introduction Cambridge University Press 2022

Aurélien Géron — Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

— Handbook of Neural Network Signal Processing

Raschka, Sebastian — Python Machine Learning

SchÃ¶lkopf, Bernhard(Author) — Learning with Kernels : Support Vector Machines, Regularization, Optimization and Beyond

Bernhard Schölkopf; Alexander J Smola — Learning with kernels : support vector machines, regularization, optimization, and beyond

D. T. Pham, P. T. N. Pham, M. S. Packianather, A. A. Afify (auth.), Diego Andina, Duc Truong Pham (eds.) — Computational Intelligence: for Engineering and Manufacturing

it-ebooks — Concise Machine Learning (UCB CS189)

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

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

Joseph S. Verducci, Xiaotong Shen, John Lafferty (ed.) — Prediction and Discovery: Ams-ims-siam Joint Summer Research Conference Machine and Statistical Learning: Prediction and Discovery June 25-29, 2006 Snowbird, Utah

Kolla Bhanu Prakash — Machine Learning for Industrial Applications

Ke-Lin Du, M. N. S. Swamy — Neural Networks and Statistical Learning

Du Ke-Lin, Swamy M.N.S — Neural networks and statistical learning

Aurelien Geron [Géron, Aurélien] — Hands-On Machine Learning with Scikit-Learn and TensorFlow

Aurelien Geron [Géron, Aurélien] — Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems

Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin — Learning From Data: A short course

Sebastian Raschka — Python Machine Learning

Patrick R. Nicolas — Scala for Machine Learning

Niladri Syam, Rajeeve Kaul — Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists

Niladri Syam, Rajeeve Kaul — Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists

Shigeo Abe (auth.) — Support vector machines for pattern classification

Ian T. Nabney — NETLAB: Algorithms for Pattern Recognition

Min Huang, Baotong Cui (auth.), Lipo Wang, Ke Chen, Yew Soon Ong (eds.) — Advances in Natural Computation: First International Conference, ICNC 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I

Andreas Miroslaus Wichert;Luis Sa-couto; — Machine Learning - A Journey to Deep Learning: With Exercises and Answers

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

Am meisten angefragte Begriffe