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Item #:
86302513
Elements of ML Programming, ML97 Edition
89% of respondents would recommend this to a friend
Item #:
86302513
€ 77
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The first book that offers BOTH a highly accessible, step-by-step introductory tutorial on ML programming and a complete explanation of advanced features.
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What Stands Out
Comprehensive Coverage
This edition provides in-depth exploration of machine learning programming concepts, ensuring readers grasp fundamental techniques and methodologies essential for data-driven applications.
Updated Content
Featuring the latest trends and advancements in machine learning, the second edition equips practitioners with current tools and practices, enhancing their ability to solve modern challenges.
Practical Examples
With real-world case studies and hands-on projects, this book bridges theory and practice, enabling readers to apply learned concepts effectively in their own ML projects.
Product Details
| Publisher | Pearson |
| Publication date | January 1, 1998 |
| Edition | 2nd |
| Language | English |
| Print length | 400 pages |
| ISBN-10 | 0137903871 |
| ISBN-13 | 978-0137903870 |
| Item Weight | 1.15 pounds (520 grams) |
| Dimensions | 9 x 0.9 x 6.9 inches (22.9 x 2.3 x 17.5 cm) |
Who Should Buy?
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Students Learning ML
Ideal for students studying ML programming, providing clear examples and comprehensive explanations of concepts.
-
Developers Working with ML
Helpful for software developers looking to enhance their skills in ML programming with practical insights and examples.
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Educators and Instructors
Useful for educators designing curricula, offering a solid foundation and structured approach to teaching ML programming.
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Beginner Programmers
Not suitable for absolute beginners, as it requires prior programming knowledge to grasp the material effectively.
Product Description
Elements of ML Programming, ML97 Edition
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Software Design, Testing & Engineering Editorial Review
**** The "Elements of ML Programming, ML97 Edition 2nd Edition" has garnered a mixed reception among its readers. For those drawn to the nuances of the ML programming language—or even those without intentions to use it—this book is lauded for its elegant Prose and engaging presentation. Many readers appreciated the author's ability to distill complex concepts, particularly praising the insightful discussions surrounding the powerful pattern matching capabilities of ML. These elements resonate not only within the context of programming but extend to broader cognitive processes. Readers found the material accessible and enjoyed the lighthearted tone and clever jokes peppered throughout the text, making it a more pleasurable read compared to other programming manuals. The book’s explanatory style has been compared favorably to well-regarded titles like Lary Wall's Perl book, characterized by a gradual approach to teaching the subject matter. However, the book does exhibit a notable flaw—many users felt a deficit in practical application. While it adeptly covers the syntax and semantics of ML, some reviewers expressed that they ended the book feeling unsure about how to implement the concepts in real-world scenarios. The focus on functional programming techniques, although well-executed, seemingly overlooked the necessity for teaching comprehensive coding style and structure that extends beyond simple examples. Additionally, readers with specific quick-reference needs voiced frustration with the book’s organization, citing challenges in locating certain programming idioms, such as accessing tuple elements or the Construction of traditional control structures. Overall, "Elements of ML Programming" serves as a commendable introduction to the principles of ML and functional programming, making it a good choice for students or novices in the field, while more advanced users may find it lacking in applied coding strategy. **
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Pros
- Beautifully written, engaging Prose
- Clear and insightful explanations, especially regarding pattern matching
- Light-hearted tone makes for enjoyable reading
- Good introduction for learners of ML and closely related languages (Haskell, Ocaml, etc.)
- Helpful for understanding functional programming concepts
Cons
- Lacks practical application guidance for real-world programming
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€ 77
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Features & Benefits
- Written by renowned computer science educator and researcher Jeffrey Ullman
- Assumes no previous knowledge of ML or functional programming
- Heavily revised and updated using ML 97
- Wide variety of program examples
- Usable in a number of courses for self-study or class discussion
- Covers both introductory and advanced features of ML programming
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