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268665114
Machine Learning: Guide for Beginners with R/Python/Scala (Paperback)
artikal br.:
268665114
RSD 2791
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Детаљи о производу
- Are you thinking of learning more about MachineLearning?(For Beginners)You will learn: Machine Learning Engineers earn on average $166,000 - become an ideal candidate withthis course!Master Machine Learning on Python, R &ScalaHave a great intuition of many Machine Learning modelsMathematical Foundation: Linear Algebra, Multivariate Calculus & Probability Theory Make powerful analysisIntroduction to Programming LanguageTools for Machine LearningIntroduction to R/Python/ScalaIntroduction to MLlib (Apache SparkLibraries of PythonDescription: Interested in the field of Machine Learning? Then this book is for you!It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions.This book and the accompanying examples, you would be well suited to tackle problems which enhance your interests using machine learning. The title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing mathematical concepts, specific algorithms, introduction to programming languages, best programming languages for Machine Learning and libraries of Python applied in Machine Learning, Download your copy now so you can get started on what is promising to be a most amazing future.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | October, 2018 |
| Pages | 84 |
| Publisher | Amazon Digital Services LLC - KDP Print US |
| Language | English |
| Edu focus | General |
| Educational level | General |
| Assembled product dimensions (l x w x h) | 5.00 x 0.17 x 8.00 in (12.7 x 0.4 x 20.3 cm) |
| Assembled product weight | 0.2 lb (90 grams) |
| Bisac subject heading | Computers |
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Machine Learning: Guide for Beginners with R/Python/Scala (Paperback)
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