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Nº de artículo:
90331072
Grokking Machine Learning
Nº de artículo:
90331072
GTQ 592
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What Stands Out
Comprehensive Approach
This book offers a holistic view of machine learning, ensuring readers grasp foundational concepts alongside practical applications, making it suitable for both beginners and those looking to deepen their knowledge.
Visual Explanations
Utilizing diagrams and illustrations, the book simplifies complex topics, helping readers visualize and understand machine learning principles better than traditional text-heavy resources.
Practical Insights
Grokking Machine Learning includes hands-on exercises that empower readers to apply theories in real-world scenarios, enhancing learning retention and bridging the gap between theory and practice.
Detalles de producto
- It's time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily available machine learning tools!In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you’re grokking as you go. You’ll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-followPython-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert.Key Features· Different types of machine learning, including supervised and unsupervised learning· Algorithms for simplifying, classifying, and splitting data· Machine learning packages and tools· Hands-on exercises with fully-explained Python code samplesFor readers with intermediate programming knowledge in Python or a similar language.About the technology Machine learning is a collection of mathematically-based techniques and algorithms that enable computers to identify patterns and generate predictions from data. This revolutionary data analysis approach is behind everything from recommendation systems to self-driving cars, and is transforming industries from finance to art.Luis G. Serrano has worked as the Head of Content for Artificial Intelligence at Udacity and as a Machine Learning Engineer at Google, where he worked on the YouTube recommendations system. He holds a PhD in mathematics from the University of Michigan, a Bachelor and Masters from the University of Waterloo, and worked as a postdoctoral researcher at the University of Quebec at Montreal. He shares his machine learning expertise on a YouTube channel with over 2 million views and 35 thousand subscribers, and is a frequent speaker at artificial intelligence and data science conferences.
| 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?
-
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.
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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.
Customer Reviews & Ratings
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ventajas
- 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
Contras
- Print length might be overwhelming for some readers
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GTQ 592
Haz tu pedido ahora y recíbelo por ahí Viernes, Noviembre 20
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