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Item #:
20991948
Building Machine Learning Powered Applications: Going from Idea to Product
Item #:
20991948
€ 47
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What Stands Out
Practical Insights
Offers real-world examples of machine learning applications, guiding readers from conceptualization to product launch, ensuring practical understanding alongside theoretical knowledge.
Comprehensive Framework
Provides a structured approach to developing machine learning projects, addressing common challenges and optimizing workflows for efficiency and effectiveness.
Expert Guidance
Written by industry professionals, this book delivers expert insights and best practices, equipping readers with the tools to successfully navigate the machine learning landscape.
Product Details
| Publisher | O'Reilly Media |
| Publication date | February 25, 2020 |
| Edition | 1st |
| Language | English |
| Print length | 257 pages |
| ISBN-10 | 149204511X |
| ISBN-13 | 978-1492045113 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 0.55 x 9.19 inches (17.8 x 1.4 x 23.3 cm) |
Who Should Buy?
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Aspiring Developers
Ideal for those looking to transform machine learning concepts into functional applications with practical guidance.
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Product Managers
Great for product managers wanting to understand machine learning integration for better decision-making and product strategies.
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Entrepreneurial Innovators
Beneficial for innovators seeking to conceptualize and launch market-ready machine learning products effectively.
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Novice Users
Not suitable for complete beginners to machine learning without prior foundational knowledge or technical background.
Product Description
Building Machine Learning Powered Applications: Going from Idea to Product
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Neural Networks Editorial Review
Building Machine Learning Powered Applications: Going from Idea to Product offers a comprehensive overview of transforming machine learning concepts into practical applications. The book, published by O'Reilly Media, is structured in a way that emphasizes best practices often overlooked by teams in fast-paced environments. Its easy-to-read narrative, drawn from the author's experiences as a data scientist, makes it suitable for both beginners and seasoned professionals looking to refine their project management skills. Comments from readers highlight the book's practical insights and structured approach, making it a valuable resource for anyone involved in machine learning product development.
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Pros
- Well-structured stages for ML product development
- Easy to read and grasp the concepts
- Practical real-world implementation insights
- Engaging narrative style for better retention
- Useful for both newbies and experienced practitioners
Cons
- Content may feel superficial for advanced users
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€ 47
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