Kolektif Kitap Machine Learning for Neat People (Computer/Technology)

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Your comprehensive entry-level guide to machine learning while machine learning expertise doesn't quite mean you can create your own turing test-proof android--as in the movie ex machina--it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems quickly and on a large scale.
Herkes bilgisayar öğreniminin ilkelerini öğrenen büyük bir bölümümüzün teknoloji geleceğinde olup, dolandırıcılık tespiti, arama sonuçlarının optimize edilmesi, gerçek zamanlı reklamların sunulması, kredi puanlaması, doğru ve karmaşık fiyatlandırma modellerinin oluşturulması gibi kariyerlerde inanılmaz yeni yönler açmaktadır. --and way, way more.
Unlike most machine learning books, the fully updated 2nd edition of machine learning for dummies doesn't assume you have years of experience using programming languages such as python (r source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks.
it takes a look at the underlying--and fascinating--math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study.
* understand the history of ai and machine learning * work with python 3. 8 and tensorflow 2. X (and r as a download) * build and test your own models * use the latest datasets, rather than the worn out data found in other books * apply machine learning to real problems whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to quickly become confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

Product information

Dimensions: Normal Size
Language of Publication: English
Year of Publication: 2020 and Before
Number of Pages: 251-300
Set/Single: One item