Published 2021
Table of Contents:
“…Understanding Probability -- The Bayesian Theorem -- The Probability Distributions for Machine Learning -- The Normal Distribution -- Supervised Learning -- The Decision Tree -- The Problem of Overfitting the Decision Tree -- The Random Forest -- Bagging -- The Naïve Bayes Method -- The KNN Algorithm -- Unsupervised Learning -- Generative Models -- Data Compression -- Association -- The
Density Estimation -- The Kernel Density Function -- Latent Variables -- Gaussian Mixture Models -- The Perceptron -- Training a Perceptron -- The Boolean Functions -- The Multiple Layer Perceptrons…”
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Taylor & Francis
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Electronic
eBook