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Grokking Machine Learning
90% of respondents would recommend this to a friend
ZAR 1537
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Discover valuable machine learning techniques you can understand and apply using just high-school math.
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What Stands Out
Product Details
| Publisher | Manning Publications |
| Publication date | 19 Jan. 2022 |
| Edition | 1st |
| Language | English |
| Print length | 350 pages |
| ISBN-10 | 1617295914 |
| ISBN-13 | 978-1617295911 |
| Item weight | 907 g |
| Dimensions | 18.75 x 3.25 x 23.5 cm |
Who Should Buy?
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Aspiring Data Scientists
Perfect for beginners who want a hands-on approach to understanding machine learning concepts and techniques.
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Self-Learners
Ideal for individuals pursuing knowledge independently and prefer a structured and comprehensive guide on machine learning.
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Professionals Switching Fields
Great for software engineers or technical professionals looking to transition into data science and machine learning roles.
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Advanced Practitioners
Not suitable for experienced data scientists seeking in-depth theoretical discussions or complex algorithm analysis.
Product Description
Grokking Machine Learning
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AI & Machine Learning Editorial Review
Grokking Machine Learning is a comprehensive guide published by Manning Publications on January 19, 2022. This first edition spans 350 pages and is designed to provide readers with a deep understanding of machine learning concepts in an accessible manner. The book, written in English, is ideal for both novices and individuals with some experience in the field. The clear explanations and engaging examples make complex topics easier to grasp, and it comes highly recommended by readers who appreciate its clarity and depth, making it a valuable resource for learning machine learning effectively.
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Pros
- Clear explanations of complex concepts
- Engaging examples for deeper understanding
- Suitable for both beginners and experienced learners
- Well-structured and easy to follow
- Comprehensive coverage of machine learning topics
Cons
- Print length might be overwhelming for some readers
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Features & Benefits
- Learn Supervised algorithms
- Data cleaning & simplification techniques
- Study Neural networks & complex dataset methods.
- No special knowledge required
- Packed with Python-based exercises & projects.
- Free eBook included with a print book purchase.
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