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Item #:
90258442
Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice, (Paperback)
84% of respondents would recommend this to a friend
Item #:
90258442
ETB 7977
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This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.
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What Stands Out
Comprehensive Coverage
This book covers a wide range of AI topics, including machine learning, deep learning, and NLP, making it an essential resource for beginners and experts alike who want to strengthen their AI programming skills.
Practical Insights
The hands-on approach enables readers to apply theoretical concepts to real-world scenarios, bridging the gap between learning and application in AI programming, particularly in reinforcement learning and deep learning.
User-Friendly Format
The easy-to-follow structure and clear explanations are designed for readers at all levels, ensuring that complex AI concepts are accessible and understandable for those new to Python programming.
Product Details
- This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models.The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered.The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable.Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.Key LearningsExplore Python basics and AI integration for real-world application and career advancement.Experience the power of Python in AI with practical machine learning techniques.Practice Python's deep learning tools for innovative AI solution development.Dive into NLP with Python to revolutionize data interpretation and communication strategies.Simple yet practical understanding of reinforcement learning for strategic AI decision making.Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI.Harness Python's capabilities for creating AI applications with a focus on fairness and bias.Table of ContentIntroduction to Artificial IntelligencePython for AIData as Fuel for AIMachine Learning FoundationEssentials of Deep LearningNLP and Computer VisionHands-on Reinforcement LearningEthics to AI
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | January, 2024 |
| Pages | 186 |
| Subgenre | Artificial Intelligence |
| Series title | No Series |
| Edition | 1 |
| Publisher | Gitforgits |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Educational level | General |
| Is collectible | N |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.50 x 0.40 x 9.25 Inches (19.1 x 1 x 23.5 cm) |
| Assembled product weight | 0.73 lb (330 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners wanting to build foundational knowledge in machine learning and artificial intelligence through practical examples.
-
Programming Enthusiasts
Great for those with Python experience who want to explore the applications of AI technologies in real-world scenarios.
-
Academic Researchers
Useful for students and researchers looking to deepen their understanding of AI, ML techniques and their practical applications.
-
Complete Beginners
Not suitable for readers with no programming or computer science background, as prior knowledge is assumed.
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Patrick J All Books Editorial Review
Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice, (Paperback) is a comprehensive guide for anyone interested in understanding the core principles of artificial intelligence. This non-fiction book, published in January 2024, spans 186 pages and covers essential topics in computing, particularly focusing on machine learning and deep learning techniques. Readers can expect to find practical insights that make complex concepts accessible. The paperback format ensures it is easy to handle while studying. This title serves as a solid foundation for learners and practitioners looking to enhance their skills in AI applications.
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Pros
- Covers essential AI programming topics thoroughly
- Accessible for general educational level
- Easy-to-handle paperback format
- Practical insights into complex AI concepts
- Focus on real-world applications of AI
Cons
- Limited to introductory level of AI concepts
Product Price History
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ETB 7977
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Features & Benefits
- Learn Python basics and their application in AI for career advancement.
- Master machine learning techniques using practical, hands-on experiences.
- Explore deep learning tools in Python for innovative AI solutions.
- Gain insights into NLP for effective data interpretation and communication.
- Understand reinforcement learning for improved strategic AI decision-making.
- Focus on ethical AI development to ensure fairness, transparency, and accountability.
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