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Machine Learning with Matlab. Superivised Learning and Regression
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Machine Learning with Matlab. Superivised Learning and Regression Paperback -

by J. Smith


From the publisher

Machine learning teaches computers to do what comes naturally to humans: learn from experience. Machine learning algorithms use computational methods to "learn" information directly from data without relying on a predetermined equation as a model. The algorithms adaptively improve their performance as the number of samples available for learning increases. Machine learning uses two types of techniques: supervised learning, which trains a model on known input and output data so that it can predict future outputs, and unsupervised learning, which finds hidden patterns or intrinsic structures in input data. This book develops supervised learning techniques and regression (Linear Regression, Generalized Linear Regression, Support Vector Machine Regression, Gaussian Procces Regression, Regression Trees, Fitting Neura Networks, Neural Networks for Time Series Prediction and Modeling, Ensemble Methods, Boosting, Random Forest and Bagging)

Details

  • Title Machine Learning with Matlab. Superivised Learning and Regression
  • Author J. Smith
  • Binding Paperback
  • Pages 402
  • Volumes 1
  • Language ENG
  • Publisher Createspace Independent Publishing Platform
  • ISBN 9781545349632 / 1545349630
  • Weight 1.75 lbs (0.79 kg)
  • Dimensions 10 x 8 x 0.82 in (25.40 x 20.32 x 2.08 cm)
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MACHINE LEARNING WITH MATLAB. SUPERVISED LEARNING AND REGRESSION
Stock Photo: Cover May Be Different

MACHINE LEARNING WITH MATLAB. SUPERVISED LEARNING AND REGRESSION

by Smith, J.

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Used
ISBN 10 / ISBN 13
9781545349632 / 1545349630
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Item Price
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Description:
n.p.: CreateSpace Independent Publishing Platform, 2017. Softcover. Quarto, 400 pages. In Very Good condition. Paperback binding. Spine blue with white lettering. Covers have minimal wear. Illustrated. 1372392. FP New Rockville Stock.
Item Price
NZ$53.62
NZ$10.21 shipping to USA