Mohssen Mohammed, Muhammad Badruddin Khan, Eihab Bashier Mohammed Bashier

Machine Learning (eBook, PDF)

Algorithms and Applications

• Format: PDF

Produktbeschreibung

Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 226
• Erscheinungstermin: 19. August 2016
• Englisch
• ISBN-13: 9781498705394
• Artikelnr.: 45534604

Autorenporträt

Mohssen Mohammed, Muhammad Badruddin Khan, Eihab Bashier Mohammed Bashier

Inhaltsangabe

Exact String Matching Algorithms. Brute
Force Algorithm. Aho
Corasick Algorithm. Boyer
Moore Algorithm. Rabin
Karp Algorithm. Knuth
Morris
Pratt Algorithm. Approximate String Matching Algorithms. Longest Common Subsequence. Longest Increasing Subsequence. Longest Common Substring. Supervised Learning. Decision Trees. C4.5 Algorithm. RIPPER Algorithm. Perceptron
Based Techniques. Naive Bayes Classifiers. Bayesian Networks. Instance
Based Learning. Support Vector Machines. Unsupervised Learning. Bayes Rule. Factor Analysis. Principal Components Analysis (PCA). Independent Components Analysis (ICA). Mixture of Gaussians. K
Means. Expectation
Maximization (EM) Algorithm. State
Space Models (Ssms). Hidden Markov Models (Hmms). Undirected Graphs. Directed Graphs. Factor Graphs.