Shallow and Deep Learning Principles: Scientific, Philosophical, and Logical Perspectives

Master the fundamentals of shallow and deep learning with a unique blend of scientific, philosophical, and logical perspectives.

This book explores:

• Artificial Neural Networks (ANNs): Understand their structure, function, and how they power prediction models.
• Shallow vs. Deep Learning: Compare and contrast their approaches, uncovering the strengths and limitations of each.
• Scientific Underpinnings: Delve into the mathematical and computational foundations of these learning methods.
• Philosophical Considerations: Explore the ethical implications and broader questions surrounding AI and machine learning.
• Logical Reasoning: Uncover the reasoning behind model design and decision-making processes.

Key benefits:

• Comprehensive: Covers both shallow and deep learning, providing a well-rounded understanding.
• Interdisciplinary: Blends scientific, philosophical, and logical perspectives for a holistic view.
• Accessible: Presents complex concepts in an understandable way, even for beginners.
• Practical: Offers insights into real-world applications of deep learning.