Machine Learning for Dummies, (Spiral Bound)
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Mastering the principles of machine learning opens up incredible new directions in careers that include fraud detection, optimizing search results, and building sophisticated pricing models.
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- 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 fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models―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 become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.
| Book format | Spiral-Bound |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | February, 2021 |
| Pages | 464 |
| Subgenre | Data Science |
| Series title | For Dummies |
| Edition | 2nd Edition |
| Publisher | Wiley |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Educational level | College |
| Is collectible | N |
| Binding type | Spiral Binding |
| Retail packaging | Single Piece |
| Assembled product height | 9.2 in |
| Assembled product weight | 1.35 lb (610 grams) |
| Bisac subject heading | Computers |
PRODUCTBESCHRIJVING
Machine Learning for Dummies, (Spiral Bound)
Vragen en antwoorden van klanten
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vraag:
Do I need prior programming experience to use this book?
antwoord: No, this book is designed for beginners and does not assume prior programming knowledge. -
vraag:
What tools will I learn to work with?
antwoord: You will learn to work with Python 3.8, TensorFlow 2.x and can also download R source code. -
vraag:
Is this book suitable for practical application?
antwoord: Yes, it focuses on using machine learning to solve real problems and includes the latest datasets for testing your models.
John Paul Mueller All Books Editorial Review
Machine Learning for Dummies, (Spiral Bound) is a comprehensive guide in the realm of computing and internet, particularly focused on data science. This non-fiction book, published in February 2021, contains 464 pages of rich content structured in a user-friendly spiral-bound format. Designed for college-level education, it effectively caters to both beginners and intermediate learners looking to enhance their understanding of machine learning concepts. Readers appreciate the clarity and step-by-step approach provided in this edition, making it an excellent resource for anyone interested in technology and data science.
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- Spiral binding allows for easy page flipping
- Comprehensive coverage of machine learning topics
- User-friendly for beginners and intermediate learners
- Engaging writing style enhances understanding
- Includes practical examples and exercises
Nadelen
- May not be comprehensive enough for advanced users
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Kenmerken en voordelen
- Fully updated 2nd Edition tailored for beginners.
- Covers essential machine learning principles without requiring prior programming knowledge.
- Learn to work with popular tools like Python 3.8 and TensorFlow 2.x.
- Access downloadable R source code with detailed comments and explanations.
- Use the latest datasets for practical applications.
- Ideal for students and professionals wanting to enhance their skills and career opportunities.
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