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Building Neural Networks from Scratch with Python

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Building Neural Networks from Scratch with Python

By: L.D. Knowings
Narrated by: Bryan Hughey
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About this listen

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.

©2023 Keyven Lewis (P)2024 Keyven Lewis Computer Science Machine Theory & Artificial Intelligence Programming Programming & Software Development Software Development Machine Learning Data Science Technology Artificial Intelligence Software

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Listener received this title free

Visual learning aids, such as diagrams, charts, and illustrations, play a crucial role in enhancing understanding and retention. This book effectively utilizes visual aids to complement textual explanations, providing visual representations of neural network architectures, optimization processes, and data transformations. These visual cues reinforce key concepts and facilitate comprehension, particularly for visual learners.

Visual Learning Aids

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Listener received this title free

A good book should strike a balance between breadth and depth. It should cover the foundational concepts comprehensively while also delving into more advanced topics like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and advanced optimization techniques.

Depth of Coverage

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In addition to technical content, the book delves into the ethical implications of neural networks and AI technologies. By addressing topics such as bias, fairness, and accountability, the book encourages readers to consider the broader societal impact of their work and emphasizes the importance of ethical decision-making in AI development. This thoughtful approach fosters a deeper understanding of the ethical challenges inherent in neural network development and encourages responsible AI practices.

Discussion of Ethical Implications

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Listener received this title free

Optimization is a critical aspect of neural network development, and this book offers practical tips for optimizing model performance and efficiency. From choosing appropriate activation functions to implementing regularization techniques, readers learn valuable strategies for improving model accuracy and preventing overfitting. These optimization tips are applicable across a wide range of neural network applications, making them invaluable for practitioners.

Practical Tips for Optimization

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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.

Practical Examples

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