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Building Neural Networks from Scratch with Python
- Narrated by: Bryan Hughey
- Length: 3 hrs and 50 mins
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Building Neural Networks from Scratch with Python
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Summary
Unlock the World of Neural Networks in Python!
Ready to dive into AI and machine learning? This guide makes it easy, even if you're a Python pro or a total beginner!
Discover how to:
- Understand the fundamentals of neural networks and their benefits
- Code without drowning in complex math equations
- Become a debugging master for efficient coding and data testing
- Stay updated on the latest tech trends and advancements
- Demystify layers, gradients, and tackle underfitting/overfitting
Transform your coding skills and knowledge with beginner-friendly projects!
Imagine a world where machine learning is accessible to all, including you. This guide will change how you perceive neural networks and propel you confidently into the realm of coding!
Don't miss this opportunity! Master neural networks and make a difference in machine learning. Click "Add to Cart" now!
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
What listeners say about Building Neural Networks from Scratch with Python
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story5 out of 5 stars
- Brendan Brady
- 23-02-24
Perfect
I've read a lot of books, both fiction and non-fiction. In fact, I typically read a book a week. But never have I read a text which is so clear, and concise. Such a perfect marriage of simplicity and information about the subject.
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Story5 out of 5 stars
- Millie Little
- 20-02-24
Coverage of Core Concepts
The book should cover core concepts of neural networks, including feed-forward and back-propagation, different activation functions, regularization techniques, and optimization algorithms.
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- Alexandra Lloyd
- 20-02-24
Up-to-Date Information
Given the rapidly evolving field of deep learning, a good book should cover contemporary techniques and best practices. It should also address popular libraries and frameworks commonly used in Python, such as TensorFlow or PyTorch.
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Cameron Saunders
- 20-02-24
Practical Examples
Readers often appreciate books that not only explain theory but also provide practical examples and code snippets. These examples should be well-commented and easy to follow.
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Lorraine Vega
- 20-02-24
Clarity and Explanation
A good book should explain complex concepts in a clear and understandable manner. It should not assume too much prior knowledge and should build up from fundamentals to more advanced topics.
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Damon Chandler
- 23-02-24
Clear Explanations of Algorithms
The book excels in providing clear explanations of neural network algorithms and techniques. Complex algorithms are broken down into manageable steps, with detailed explanations of each component. This clarity helps demystify neural networks and enables readers to understand not just how algorithms work, but why they work, empowering them to adapt and apply these techniques to new problems.
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Betsy Gregory
- 23-02-24
Structured Learning Path
This book offers a structured learning path that guides readers through the fundamentals of neural networks to more advanced topics. Each chapter builds upon the concepts introduced in the previous ones, providing a cohesive and organized approach to learning. This structure ensures that readers develop a solid foundation before tackling more complex material, fostering deeper comprehension and retention.
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Story5 out of 5 stars
- Alicia Gonzales
- 20-02-24
Hands-On Exercises
Exercises and projects help reinforce learning. A good book might include exercises at the end of each chapter or provide larger projects that readers can work on to deepen their understanding.
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Betty Alvarado
- 21-02-24
Historical Context and Milestones
Providing historical context by discussing the evolution of neural network architectures, key milestones, and influential research papers can help readers appreciate the progress and significance of the field.
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Overall5 out of 5 stars
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- Oscar Hussain
- 21-02-24
Code Readability and Style
Beyond just providing code snippets, a good book should emphasize clean, readable code that follows best practices. Consistent formatting, meaningful variable names, and well-commented sections contribute to a more enjoyable learning experience.
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