Andrew Trask Books
Andrew Trask is a researcher in machine learning and artificial intelligence. He has worked on privacy-preserving deep learning and is known for his contributions to the OpenMined community.
Known for: Grokking Deep Learning
Books by Andrew Trask
Grokking Deep Learning
Grokking Deep Learning is an accessible introduction to the fundamentals of deep learning. Written for readers with minimal mathematical background, it explains neural networks from first principles, showing how they learn and make predictions. The book guides readers through building their own neural networks from scratch in Python, helping them understand the underlying mechanics of backpropagation, gradient descent, and other core concepts.
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Learning from Data: The Motivation Behind Deep Learning
In the beginning, all learning—human or machine—starts with a question: how can we make predictions from experience? When a child learns to recognize a cat, they are unconsciously forming a mapping between sensory inputs and conceptual outputs. Machines, too, must learn such mappings. In this chapte...
From Grokking Deep Learning
Simple Functions: Representing Relationships Between Inputs and Outputs
The heart of all machine learning, and indeed all modeling, rests on mathematical functions. A function is a relationship—input goes in, output comes out. In this chapter, I guide you through how even the simplest functions can model real-world phenomena, and how they become the bricks from which ne...
From Grokking Deep Learning
About Andrew Trask
Andrew Trask is a researcher in machine learning and artificial intelligence. He has worked on privacy-preserving deep learning and is known for his contributions to the OpenMined community. Trask’s work focuses on making AI more understandable and accessible to a broad audience.
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Andrew Trask is a researcher in machine learning and artificial intelligence. He has worked on privacy-preserving deep learning and is known for his contributions to the OpenMined community.
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