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Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. Summary We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning in...
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Now in its second edition, Introduction to Finite Element Analysis for Engineers is an essential introduction to FEA as a method to solve differential equations. With many practical examples focusing on both solid mechanics and fluid mechanics, it includes problems for both applications. Using a structure of classes of differential equations, the book also includes MATLAB® codes and aims to build a comprehensive understanding of FEA and its applications in modern engineering. New chapters present finite-element models of a system of partial differential equations in two or more independent variables typified by problems in theory of elasticity and plates. Chapter ten presents the finite ele...