A Greater Foundation For The Triumph Of Deep Learning With XAI

A Greater Foundation For The Triumph Of Deep Learning With XAI
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Asimov back in the day, to avoid the perils and dangers of robots taking over the humans, set three rules to restrict the behaviour of robots, such as a robot cannot hurt a human or injure and a robot must always obey the orders except where there’s a conflict to the first law. At the same time, the robot should protect their own existence without any conflict to first law and second law. Instead of encoding the robots with millions of rules, empowering the robots to choose the right solution in a dynamic environment with both discrete and continuous spaces would help understand the behaviour of the robotics or machine learning algorithms.  The book covers XAI white-box models for the explainability and interpretability of algorithms with transparency for the accuracy of the pred
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Ganapathi Pulipaka
Dr Ganapathi Pulipaka is Chief AI HPC Scientist and bestselling author of books covering AI infrastructure, supercomputing, high-performance computing for HPC, parallel computing, neural network architecture, data science, machine learning, and deep learning in C, C++, Java, Python, R, TensorFlow, and PyTorch on Linux, macOS, and Windows.
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