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20047112
Mastering Machine Learning Algorithms: Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and
89% of respondents would recommend this to a friend
Item #:
20047112
€ 62
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Giuseppe Bonaccorso is a highly accomplished data scientist with a strong background in machine learning and big data.
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What Stands Out
Comprehensive Techniques
This book covers a wide range of machine learning algorithms, providing expert techniques for implementing and fine-tuning models, making it an indispensable guide for both beginners and experienced practitioners.
In-depth Understanding
It emphasizes not just implementation but also understanding the inner workings of algorithms, ensuring readers can rigorously analyze and adapt models for their specific use cases.
Updated Edition
The 2nd edition includes the latest advancements in machine learning, ensuring that you are equipped with current strategies and methodologies essential for staying competitive in the rapidly evolving tech landscape.
Product Details
| Publisher | Packt Publishing |
| Publication date | January 31, 2020 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 798 pages |
| ISBN-10 | 1838820299 |
| ISBN-13 | 978-1838820299 |
| Item Weight | 3.15 pounds (1.43 kg) |
| Dimensions | 7.5 x 1.8 x 9.25 inches (19.1 x 4.6 x 23.5 cm) |
Who Should Buy?
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Aspiring Data Scientists
Ideal for beginners seeking a comprehensive understanding of machine learning techniques and practical implementation strategies.
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Experienced Practitioners
Provides advanced insights and fine-tuning techniques appealing to those already familiar with basic algorithms.
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Academic Researchers
Useful for researchers who need a solid reference to machine learning algorithms and their underlying principles.
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Complete Beginners
Not suitable for individuals with no background in programming or basic statistics, as it assumes prior knowledge.
Product Description
Mastering Machine Learning Algorithms: Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work, 2nd Edition
About This Item
Are you looking to expand your knowledge and skills in the field of machine learning? Look no further than "Mastering Machine Learning Algorithms: Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work, 2nd Edition." Written by Giuseppe Bonaccorso, a highly experienced Head of Data Science in a large multinational company, this book provides an in-depth understanding of advanced machine learning algorithms. Whether you are a beginner or an experienced practitioner, this comprehensive guide will enhance your understanding and mastery of machine learning. In this 2nd edition, Bonaccorso dives deep into popular machine learning algorithms and provides expert techniques for implementing them effectively. From regression and classification to clustering and anomaly detection, this book covers it all.
You will learn to predict, classify, and cluster data accurately using Python, one of the most popular programming languages for machine learning. What sets this book apart is the author's emphasis on understanding how these algorithms work. You will not only learn how to apply them but also gain insights into their inner workings. This knowledge will enable you to fine-tune your models and optimize their performance for different use cases. With "Mastering Machine Learning Algorithms," you will embark on a learning journey that covers a wide range of topics, including natural language processing, recommendation systems, time series analysis, image recognition, sentiment analysis, fraud detection, and healthcare analytics.
Each topic is explained in a clear and concise manner, making it accessible to both beginners and experts alike. Giuseppe Bonaccorso's expertise in machine learning shines through in this book, which is a result of his extensive research and practical experience. His previous publications, including "Machine Learning Algorithms" and "Hands-On Unsupervised Learning with Python," have received praise from both academia and industry professionals. If you are serious about mastering machine learning and want to stay ahead in this rapidly evolving field, "Mastering Machine Learning Algorithms" is a must-have resource. Start your journey towards becoming a machine learning expert today!.
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Customer Questions & Answers
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Question:
What is Giuseppe Bonaccorso's educational background?
Answer: He holds an M.Sc.Eng. in Electronics from University of Catania, Italy, and continued his studies at University of Rome Tor Vergata and University of Essex, UK. -
Question:
What are Giuseppe Bonaccorso's main interests?
Answer: His main interests include machine/deep learning, reinforcement learning, big data, and bio-inspired adaptive systems. -
Question:
What publications has Giuseppe Bonaccorso authored?
Answer: He is the author of several publications including Machine Learning Algorithms and Hands-On Unsupervised Learning with Python, published by Packt.
Machine Theory Editorial Review
The "Mastering Machine Learning Algorithms" book is a solid resource for learning and understanding popular machine learning algorithms. The book complements other manuals, such as "Python Machine Learning." However, the mathematical notation is not always precise, creating confusion and errors for readers. The coding in the book is not always clean, and there are many code duplications, making the book challenging to read. Additionally, there are some errors fundamental to the material, meaning readers might need to spend valuable time proofreading instead of learning new material. The book is not for beginners, and readers must already have sufficient knowledge in machine learning. The book provides a thorough explanation of the mathematical nature of data and algorithms, making it a good choice for experts looking to deepen their knowledge.
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Pros
- Solid resource for learning popular machine learning algorithms.
- Complements other manuals, such as "Python Machine Learning."
- Provides thorough explanations of the mathematical nature of data and algorithms.
- Covers a wide variety of topics, such as Hebbian Learning, Graphical Models, and Bayesian Networks.
Cons
- Mathematical notation is not always precise, creating confusion and errors.
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Features & Benefits
- Head of Data Science in a large multinational company.
- M.Sc.Eng. in Electronics from University of Catania, Italy.
- Continued studies at University of Rome Tor Vergata and University of Essex, UK.
- Expertise in machine/deep learning, reinforcement learning, big data, and bio-inspired adaptive systems.
- Author of several publications including Machine Learning Algorithms and Hands-On Unsupervised Learning with Python.
- Highly accomplished in the field of data science.
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