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Numéro d'article:
21847267
Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series) 1st Edition
90% des répondants recommanderaient ceci à un ami
Numéro d'article:
21847267
CAD 57
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Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use.
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Ce qui se démarque
Comprehensive Overview
Covers essential machine learning concepts tailored for beginners, ensuring readers grasp both foundational principles and practical applications, making it accessible and informative for aspiring data scientists.
Hands-On Approach
Includes real-world examples and practical exercises, allowing readers to apply what they've learned in Python, enhancing skill acquisition and confidence in machine learning implementations.
Reader-Friendly Format
Utilizes a clear, engaging writing style and structured chapters, which facilitate understanding and retention of complex ideas, catering specifically to non-experts in the field of data analytics.
Détails du produit
- Comprehensive guide to understanding and building machine learning systems with Python
- Suitable for absolute beginners with basic Python coding skills and minimal college-level math knowledge
- Communicates machine learning ideas through plain-English stories, pictures, and Python examples
- Covers key mathematical and computational topics in an approachable manner
- Discusses building, training, and evaluating learning systems, and explores advanced techniques
- Includes practical insights applicable to various learning systems, and leverages Python scikit-learn library and other powerful tools
| Package Weight | 2.1000 Pound |
À qui est-ce destiné ?
-
Beginners in ML
Ideal for newcomers to machine learning, providing foundational concepts and easy-to-understand examples.
-
Python Enthusiasts
Beneficial for Python developers looking to understand machine learning applications and implementations within the language.
-
Data Analysts
Great for data analysts wanting to expand their skill set with machine learning techniques and practical examples.
-
Advanced Practitioners
Not suitable for experts seeking advanced algorithms or in-depth theoretical discussions on machine learning.
DESCRIPTION DU PRODUIT
Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series) 1st Edition
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Product Buying Guide
Machine Learning with Python for Everyone is a comprehensive beginner's guide to understanding and building machine learning systems with Python. The book is designed to help individuals master the processes, patterns, and strategies required to create effective learning systems, regardless of their level of expertise in Python programming or college-level math knowledge.
Product Specifications
- Book Title: Machine Learning with Python for Everyone
- Series: Addison-Wesley Data & Analytics Series
- Edition: 1st Edition
- Author: Mark E. Fenner
- Language: English
- Format: Paperback
- Number of Pages: Variable
- Publisher: Addison-Wesley Professional
Key Features
- Introduces key mathematical and computational topics in an approachable manner
- Walks through the first steps in building, training, and evaluating learning systems
- Explores sophisticated and exciting machine learning techniques
- Provides insights applicable to every learning system individuals build or use
- Covers machine learning algorithms, models, and core concepts
- Connects core concepts to neural networks and graphical models
- Includes access to downloads, updates, and corrections
Usage Scenarios
- Ideal for students, analysts, scientists, or hobbyists interested in machine learning
- Useful for individuals looking to understand and leverage Python for machine learning
- Applicable for those seeking to realistically assess performance of machine learning systems
Usage Scenarios
The book competes with similar titles in the market, offering a comprehensive and beginner-friendly approach to machine learning with Python. It distinguishes itself by its focus on plain-English stories, pictures, and Python examples to communicate machine learning ideas, making it highly approachable for beginners and individuals with limited math background.
Some User Review
- Readers appreciate the clear and concise explanations, making complex machine learning concepts easily understandable.
- Many users commend the practical examples and Python code provided, aiding in the understanding and implementation of machine learning techniques.
- The book's focus on real-world applications and practical insights has received positive feedback from readers across various backgrounds.
Competitors
The book is competitively priced within the machine learning literature segment, offering a comprehensive and beginner-friendly approach to machine learning with Python.
Buying Considerations
- Consider your current proficiency in Python programming and college-level math knowledge to ensure the book aligns with your learning needs.
- Evaluate your interest in real-world applications and practical insights to gauge the relevance of the content provided.
- Compare the book's price with similar titles in the market to make an informed purchasing decision.
Conclusion
Machine Learning with Python for Everyone is the ideal resource for individuals looking to gain a fundamental understanding of machine learning and its practical application using Python. With its beginner-friendly approach, clear explanations, and practical examples, this book is a valuable asset for students, analysts, scientists, or hobbyists interested in delving into the world of machine learning.
Voir moinsMachine Learning with Python for Everyone is a comprehensive beginner's guide to understanding and building machine learning systems with Python. The book is designed to help individuals master the processes, patterns, and strategies required to create effective learning systems, regardless of their level of expertise in Python programming or college-level math knowledge. Continue Reading
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Intelligence & Semantics Editorial Review
**** "Machine Learning with Python for Everyone" by Dr. Mark Fenner has been positively received by a diverse audience, particularly those with little formal training in machine learning. The book is crafted with clarity and accessibility, making complex topics more palatable for beginners. Dr. Fenner acknowledges the common hurdles that newcomers face in the realm of machine learning, especially when grappling with mathematical concepts. He intentionally simplifies the approach by using storytelling, graphical illustrations, and practical Python code, rather than overwhelming readers with heavy mathematics. While the book covers various aspects of developing predictive models, it's not structured as a comprehensive tutorial on setting up a development environment. It assumes that readers come with a fundamental knowledge of Python and are comfortable with basic charts and graphs. Some feedback points to a desire for a hands-on workbook that enables readers to run examples directly, which might limit its immediate applicability for those looking for a plug-and-play experience. Readers appreciate Dr. Fenner's informal writing style and the engaging manner in which he presents the material. Many commend the book for its practical examples, which allow readers to see real-world applications of the concepts discussed. There’s a Consensus among reviewers that the content is relevant and up to date, providing valuable insights into machine learning. Overall, "Machine Learning with Python for Everyone" has emerged as a commendable resource for individuals starting their journey in machine learning, particularly for those preferring an approachable introduction rather than an arithmetic-heavy discourse. **
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Avantages
- Clear and accessible writing for beginners.
- Minimizes complex mathematics while introducing concepts.
- Informal and engaging style that simplifies learning.
- Practical examples in Python make concepts relatable.
- Up-to-date information relevant to current data science scenarios.
- Responsive author engaging with readers for clarifications.
Les inconvénients
- Lacks a comprehensive tutorial on setting up a development environment.
Historique des prix du produit
Informations importantes
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Caractéristiques et avantages
- Master machine learning processes with Python
- Perfect for absolute beginners with minimal math knowledge
- Build, train, and evaluate learning systems step by step
- Learn core concepts, techniques, and sophisticated methods
- Applicable to every learning system for students, analysts, scientists, or hobbyists
- Includes access to downloads, updates, and corrections
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