Machine learning: algorithms and applications by Mohssen Mohammed, Muhammad Badruddin Khan, Eihab Bashier PDF

By Mohssen Mohammed, Muhammad Badruddin Khan, Eihab Bashier Mohammed Bashier

Machine studying, one of many best rising sciences, has an exceptionally vast variety of purposes. even though, many books at the topic supply just a theoretical strategy, making it tricky for a newcomer to understand the subject matter. This publication presents a simpler technique via explaining the recommendations of laptop studying algorithms and describing the parts of program for every set of rules, utilizing uncomplicated useful examples to illustrate every one set of rules and displaying how diverse concerns on the topic of those algorithms are applied.

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Although machines are expected to do mechanical jobs much faster than humans, it is not expected from a machine to: understand the play Romeo and Juliet, jump over a hole in the street, form friendships, interact with other machines through a common language, recognize dangers and the ways to avoid them, decide about a disease from its symptoms and laboratory tests, recognize the face of the criminal, and so on. The challenge is to make dumb machines learn to cope correctly with such situations.

In the second section, we discuss the k-means, Gaussian mixture model, hidden Markov model, and principal component analysis in the context of dimensionality reduction. We have written the chapters in such a way that all are independent of one another. That means the reader can start from any chapter and understand it easily. MATLABŴ is a registered trademark of The MathWorks, Inc. For product information, please contact: The MathWorks, Inc. com Acknowledgments We are deeply thankful to all those who have contributed directly or indirectly to the publication of this book.

6 The top 10 strategic technologies in years 2014 and 2015. In their prediction related to smart machines for 2014 and 2015, the following statements were made: By 2015, there will be more than 40 vendors with commercially available managed services offerings leveraging smart machines and industrialized services. By 2018, the total cost of ownership for business operations will be reduced by 30% through smart machines and industrialized services. Through 2020, the smart machine era will blossom with a proliferation of contextually aware, intelligent personal assistants, smart advisors (such as IBM Watson), advanced global industrial systems, and public availability of early examples of autonomous vehicles.

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