Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Ease Machine Learning: For Entrepreneurs, Administrators and Innovators

Ease Machine Learning: For Entrepreneurs, Administrators and Innovators

Viera Balanta, Víctor
Palacios Medina, Maritza

Paperback

General Education

ISBN13: 9798662779341
Publisher: Independently Published
Published: Jun 30 2020
Pages: 194
Weight: 1.02
Height: 0.41 Width: 8.50 Depth: 11.02
Language: English
Welcome, Machine Learning strategies are oriented to support business decision making. With well-designed models and adequate data, you can literally predict the future (keep in mind that there are futures that can be predicted with Machine Learning and others that cannot), gain competitive advantage, and make innovations. And if the above seems too little, with Machine Learning strategies you can know the behavior of clients or competitors, and therefore, anticipate their movements.Remember that: Machine learning is magical. You give it data and it manages to classify that data. For many, it can actually outperform a human! But, like so many problems in the world, there is a significant garbage in, garbage out aspect to machine learning. If the data you give it is trash, the learning algorithm is unlikely to be able to overcome it ( Daumé III, 2014, pag. 51)In this sense, by reading this book and applying its steps, they can learn about Machine Learning in the field of supervised learning. In this way, being a book aimed at entrepreneurs, administrators and innovators.In this way, the book presents Machine Learning models with simple data that is easy to understand. Each example contains specific elements for understanding those who do not want to know anything about the complex mathematics behind the Machine Learning models. Likewise, specific elements are also presented for those who are curious to know what moves or how it moves or what are the mechanisms with which Machine Learning performs its wonderful processes. In other words, if we place ourselves in a university environment, the book may be in the hands of a student or professor of an administration program or an engineering program. Although I love mathematics because of my profession as an engineer, I must mention that with the book you can learn Machine Learning without the need to strictly approach the mathematics..it presents an approach with practical examples supported by the software Orange (University of Ljubljana).

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