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Machine Learning: Algorithms and Applications
— —
Mohssen Mohammed (Al-Imam Muhammad Ibn Saud University, Saudi Arabia) Muhammad Badruddin Khan (Imam Muhammad Ibn Saud University, Riyadh, Saudi Arabia)
Machine Learning: Algorithms and Applications by Mohssen Mohammed (Al-Imam Muhammad Ibn Saud University, Saudi Arabia) at Abbey's Bookshop,

Machine Learning: Algorithms and Applications

Mohssen Mohammed (Al-Imam Muhammad Ibn Saud University, Saudi Arabia) Muhammad Badruddin Khan (Imam Muhammad Ibn Saud University, Riyadh, Saudi Arabia) Eihab Bashier Mohammed Bashier (Faculty of Sciences and Arts in Baljurashi at Albaha University, Saudi Arabia)


9781498705387

Productivity Press


Algorithms & data structures;
Machine learning


Hardback

204 pages

$137.00
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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.

By:   Mohssen Mohammed (Al-Imam Muhammad Ibn Saud University Saudi Arabia), Muhammad Badruddin Khan (Imam Muhammad Ibn Saud University, Riyadh, Saudi Arabia), Eihab Bashier Mohammed Bashier (Faculty of Sciences and Arts in Baljurashi at Albaha University, Saudi Arabia)
Imprint:   Productivity Press
Country of Publication:   United States
Dimensions:   Height: 235mm,  Width: 156mm,  Spine: 23mm
Weight:   454g
ISBN:   9781498705387
ISBN 10:   1498705383
Pages:   204
Publication Date:   July 2016
Audience:   General/trade ,  College/higher education ,  Professional and scholarly ,  ELT Advanced ,  Primary
Format:   Hardback
Publisher's Status:   Active

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.

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