What is 'AI and Machine Learning for Coders' about?

'AI and Machine Learning for Coders' is a comprehensive guide designed for programmers who want to delve into the world of artificial intelligence and machine learning. The book focuses on practical applications, teaching readers how to implement AI solutions using popular programming languages. By incorporating real-world examples and hands-on exercises, the book caters to both beginners and experienced coders, making complex concepts approachable.

Who is the target audience for this book?

The target audience for 'AI and Machine Learning for Coders' primarily includes software developers, data scientists, and computer science students who are keen to learn about AI. The content is structured to cater to various skill levels, from those new to programming to seasoned coders looking to expand their expertise in cutting-edge AI technologies. By providing practical insights and applications, it equips readers with the tools they need to tackle AI projects effectively.

What programming languages are covered in this book?

'AI and Machine Learning for Coders' covers a range of programming languages, with a strong emphasis on Python due to its popularity and robustness in the data science community. The book also addresses frameworks and libraries such as TensorFlow and PyTorch, enabling readers to develop machine learning applications. This diverse approach ensures that readers can easily integrate AI techniques into their existing projects, regardless of their preferred coding language.

Can beginners understand this book?

Yes, beginners can certainly understand 'AI and Machine Learning for Coders'. The book starts with foundational concepts before gradually introducing more complex topics. It includes clear explanations, diagrams, and step-by-step tutorials that facilitate learning. By following the structured approach, even those with basic programming knowledge can gain a strong grasp of AI and machine learning applications.

How does this book differ from other AI books?

'AI and Machine Learning for Coders' differentiates itself through its practical, hands-on approach. Unlike many theoretical AI texts, this book focuses on real-world applications and includes coding exercises that allow readers to implement what they've learned immediately. This blend of theory and practice empowers readers to understand not just the how, but also the why behind AI algorithms and techniques, making it a valuable resource for practical developers.

Are there any prerequisites to read this book?

While 'AI and Machine Learning for Coders' can be beneficial for readers with varying backgrounds, familiarity with at least one programming language is strongly recommended. Understanding basic programming concepts, such as loops, functions, and data structures will enhance the learning experience. This foundational knowledge allows the reader to grasp the machine learning code examples presented in the book more effectively.

What types of AI projects can I build after reading this book?

After reading 'AI and Machine Learning for Coders', you can embark on various AI projects, including predictive modeling, natural language processing applications, and computer vision tasks. For example, you could build a chatbot, develop a recommendation system, or create an image classification model. These practical projects not only reinforce the concepts learned but also provide tangible outcomes that can be showcased in a portfolio.

Is this book suitable for self-study?

Absolutely! 'AI and Machine Learning for Coders' is designed with self-study in mind. Each chapter contains hands-on exercises and challenges that encourage independent learning. Plus, the clear explanations and structured layout allow readers to learn at their own pace. This makes it an excellent resource for those looking to enhance their skills without formal instruction or classroom settings.

What additional resources accompany this book?

The book 'AI and Machine Learning for Coders' typically comes with supplementary online resources. These may include access to code repositories, online forums, or video tutorials that complement the reading material. Such resources provide further insights and community support, enhancing the learning experience by allowing readers to collaborate and share knowledge with others exploring AI and machine learning.

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AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

A hands-on, code-first approach to help you build confidence while you learn key topics

Numéro d'article: 37162050

AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

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You can buy 'AI and Machine Learning for Coders: A Programmers Guide to Artificial Intelligence 1st Edition' from Ubuy in Mali. Ubuy offers a convenient online shopping experience, allowing you to browse, order, and receive the book right at your doorstep. It’s a reliable platform that ensures a smooth purchasing process, excellent customer service, and various shipping options tailored for your needs.

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Ce qui se démarque

Accessible Learning

Designed specifically for programmers, this book simplifies complex AI concepts, enabling coders to grasp essential principles without prior AI experience.

Practical Applications

Focuses on real-world coding examples, empowering users to integrate AI tools effectively in their projects and improve problem-solving capabilities.

Comprehensive Resources

Provides a wealth of resources, including code snippets and exercises, to enhance learning and foster hands-on experience in machine learning.

Détails du produit

Designed for programmers looking to transition into AI specialization
Hands-on, code-first approach to build confidence while learning key topics
Covers common machine learning scenarios: computer vision, NLP, and sequence modeling
Practical lessons with code samples, avoiding complex math
Includes TensorFlow skills desired by employers
Teaches embedding models in Android, iOS, and serving models in web and cloud with TensorFlow Serving

Publisher	O'Reilly Media
Publication date	November 10, 2020
Edition	1st
Language	English
Print length	390 pages
ISBN-10	1492078190
ISBN-13	978-1492078197
Item Weight	2.31 pounds (1.05 kg)
Reading age	1 year and up
Dimensions	7 x 1.25 x 9 inches (17.8 x 3.2 x 22.9 cm)

À qui est-ce destiné ?

Aspiring Data Scientists
Ideal for individuals looking to transition into data science, providing foundational knowledge of AI and machine learning.
Software Developers
Beneficial for programmers who want to incorporate AI techniques into their software applications for enhanced functionality.
Tech Enthusiasts
Great for hobbyists interested in emerging technologies, offering hands-on projects to ignite curiosity in AI.

Complete Beginners
Not suitable for those with no programming experience, as it assumes prior coding knowledge and familiarity.

DESCRIPTION DU PRODUIT

AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

About This Item

Introducing "AI and Machine Learning For Coders: A Programmer's Guide to Artificial Intelligence Paperback – Large Print, 16 Oct. 2020" Are you a programmer looking to dive into the fascinating world of artificial intelligence and machine learning? Look no further! "AI and Machine Learning For Coders" is the ultimate guide to empower you with the knowledge and skills needed to excel in this exciting field. This comprehensive book is specifically designed for programmers like you who are eager to understand the inner workings of AI and machine learning. Whether you're a beginner or an experienced coder, this guide is packed with valuable insights and practical examples that will help you master the concepts and applications of AI in no time. With its large print format, this paperback edition ensures optimal readability, making it easy for you to follow along and grasp complex concepts.

This means you can focus on learning without any unnecessary eye strain or fatigue. Inside the pages of this book, you will find a systematic and step-by-step approach to understanding the fundamentals of AI and machine learning. From foundational concepts to advanced techniques, you'll discover how to develop intelligent systems that can analyze data, make predictions, and improve their performance over time. Key Topics Covered: - The Basics of AI and Machine Learning - Essential Algorithms and Data Structures - Supervised and Unsupervised Learning - Neural Networks and Deep Learning - Natural Language Processing - Computer Vision and Image Recognition - Reinforcement Learning - Ethical Considerations in AI Designed as a programmer's guide, this book goes beyond just theory. It offers practical examples, real-world case studies, and hands-on exercises that allow you to apply your newfound knowledge to practical scenarios.

This approach ensures that you not only understand the concepts but also gain the necessary skills to implement AI and machine learning techniques in your own projects. Stay ahead of the curve and unlock the potential of AI and machine learning in your coding journey. Order your copy of "AI and Machine Learning For Coders: A Programmer's Guide to Artificial Intelligence" today and take your programming skills to new heights.

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Intelligence & Semantics Editorial Review

The book "AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence 1st Edition" by Laurence Moroney provides practical and understandable explanations of coding machine learning into different environments using TensorFlow. The author gives good starter discussion on ML techniques and examples of neural networks that are intuitive. However, some customers reported misaligned sample codes with those in the GitHub repository, suggesting that the codes may not be properly tested. The last chapter on ethics and federated learning felt short, and some difficult to understand topics were not explained in-depth. Nevertheless, some customers praised the book as being practical and directly applicable to real-world problems, with examples that might directly solve problems one may be contemplating using TensorFlow for. Others commended the author for explaining tough concepts in an easy-to-understand way, and the absence of math in the book. Some customers recommend the book in combination with Laurence's videos on YouTube to build a solid foundation in deep learning.

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Avantages

Provides practical and understandable explanations
Good starter discussion on ML techniques
Examples of neural networks are intuitive
Helpful code samples
Practical and directly applicable to real-world problems
Good "cookbook" for both using TensorFlow and deploying TensorFlow models to alternate/resource-Constrained devices
Author explains tough concepts in an easy-to-understand way
Math is almost absent in the book

Les inconvénients

Some sample codes misalign with those in the GitHub repository

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Caractéristiques et avantages

Learn AI and Machine Learning for Coders from scratch
Practical lessons with direct code implementation
Get a comprehensive knowledge of computer vision, NLP, and sequence modeling
Build models with TensorFlow and deploy them on various platforms
A beginner-friendly guide without advanced math requirements
Ideal for programmers looking for a career move in AI

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AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

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Ce qui se démarque

Détails du produit

À qui est-ce destiné ?

DESCRIPTION DU PRODUIT

About This Item

Questions et réponses des clients

Intelligence & Semantics Editorial Review

Avis et évaluations clients

Donnez votre avis sur ce produit

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Les inconvénients

Historique des prix du produit

Informations importantes

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