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Item #:
88845178
Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)
89% of respondents would recommend this to a friend
Item #:
88845178
ZMW 1011
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Learn to unleash the power of AI creativity with practical skills in Python for Generative AI applications.
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What Stands Out
Comprehensive Coverage
This book offers an in-depth exploration of Python's generative AI, covering autoencoders, transformers, and large language models, providing a thorough foundation for both beginners and advanced learners.
Practical Applications
Each concept is paired with practical applications, ensuring readers can not only understand the theory but also implement generative AI solutions in real-world scenarios, enhancing skill development.
Up-to-Date Insights
Staying current with the latest trends, this edition includes modern techniques and frameworks, ensuring readers are equipped with the most relevant knowledge to excel in the rapidly evolving field of AI.
Product Details
| Publisher | BPB Publications |
| Publication date | February 1, 2024 |
| Language | English |
| Print length | 348 pages |
| ISBN-10 | 9355518978 |
| ISBN-13 | 978-9355518972 |
| Item Weight | 1.3 pounds (590 grams) |
| Dimensions | 7.5 x 0.79 x 9.25 inches (19.1 x 2 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for those looking to enter the fields of data science and machine learning using Python.
-
AI Enthusiasts
Perfect for individuals eager to explore generative AI concepts and their applications in modern technology.
-
Developers Transitioning
Beneficial for software developers aiming to shift into AI development, preparing them for advanced topics.
-
Beginner Programmers
Inadequate for those with little or no programming knowledge, as foundational skills are needed.
Product Description
Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)
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Customer Questions & Answers
-
Question:
What topics does the book 'Learn Python Generative AI' cover?
Answer: This book dives deep into the fascinating world of generative AI, starting from foundational concepts like autoencoders, moving through to more advanced topics such as transformers and large language models. Readers will explore theory and practical applications, helping them understand how these models function and how to implement them in Python. The comprehensive approach makes it useful for both beginners and advanced practitioners looking to enhance their knowledge and skills. -
Question:
Is this book suitable for beginners in AI and Python?
Answer: Absolutely! 'Learn Python Generative AI' is structured to accommodate readers with varying levels of expertise. Beginners are guided through the essential concepts of Python programming and machine learning before being introduced to more complex AI models. The book uses clear language and practical examples, making it a practical resource for anyone looking to start their generative AI journey. -
Question:
What programming language is primarily used in the book?
Answer: The book primarily uses Python as its programming language for coding examples and illustrations. Python is favored in the AI community due to its simplicity and the vast availability of libraries like TensorFlow and PyTorch, which facilitate the implementation of various models. Readers will gain hands-on experience by following along with the coding practices provided throughout the chapters. -
Question:
Can this book help me understand large language models?
Answer: Yes, 'Learn Python Generative AI' thoroughly explores large language models, delving into their architecture, functioning, and various applications. By providing detailed explanations and practical coding exercises, the book equips readers with the knowledge to not only understand but also build and fine-tune such models for specific tasks, such as text generation and natural language processing. -
Question:
Are there any practical exercises included in the book?
Answer: Yes, the book includes a variety of practical exercises, allowing readers to apply what they learn in real-time. Each chapter comes with coding tasks that reinforce the concepts discussed, enabling readers to write their own generative AI programs. This hands-on approach is designed to solidify understanding and boost problem-solving skills in practical scenarios. -
Question:
How does this book compare to others on AI and machine learning?
Answer: 'Learn Python Generative AI' stands out due to its focused approach on generative models, providing a specialized curriculum that might not be extensively covered in other books. It balances theoretical insights and practical coding, making it suitable as both a learning tool and a reference guide. Readers benefit from detailed discussions that bridge the gap between concepts and real-world applications, thus enhancing overall comprehension. -
Question:
Will I need prior experience in machine learning to understand the content?
Answer: No prior experience is strictly necessary to grasp the content of 'Learn Python Generative AI.' While familiarity with programming is beneficial, the book starts with a foundational overview of machine learning concepts that will help new learners build confidence. Throughout the chapters, complex ideas are broken down into manageable sections, ensuring that readers can follow along regardless of their background. -
Question:
What is the target audience for this book?
Answer: The target audience for 'Learn Python Generative AI' includes aspiring data scientists, software developers, and anyone interested in AI and machine learning. Both beginners looking to start their journeys and seasoned professionals wanting to expand their skills in generative AI will find value in the content. It serves as a great resource for academic courses or personal study. -
Question:
Can you explain the significance of transformers in AI?
Answer: Transformers are revolutionary architectures in AI, particularly in natural language processing tasks. They enable models to process sequences of data (like text) by considering the context of all words simultaneously, rather than sequentially. This leads to improved understanding and generation of human language, making transformers a key component in many advanced AI applications, such as translation services and chatbots featured in modern tech. -
Question:
Where can I buy 'Learn Python Generative AI' in Zambia?
Answer: You can purchase 'Learn Python Generative AI: Journey from autoencoders to transformers to large language models English Edition' at Ubuy, which provides a seamless shopping experience for this insightful resource.
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Pros
- Comprehensive coverage of topics
- User-friendly explanations
- Engaging practical examples
- Suitable for beginners and experts
- Well-structured learning path
Cons
- Some sections may be too advanced for complete beginners.
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Features & Benefits
- Discover core concepts and applications of generative AI.
- Learn to design neural networks using Python and TensorFlow.
- Explore practical impacts in healthcare, retail, and finance.
- Access advanced content made approachable for learners.
- Understand the integration of SWIN-Transformer in generative AI.
- Empower your skills with real-world examples and innovative solutions.
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