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Find a path to becoming a Automated Systems. Learn more at:
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Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Automated Systems.
Provides a comprehensive overview of automated systems, covering topics such as system design, modeling, analysis, and control. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of automated systems.
Provides a comprehensive introduction to modern control systems. It covers topics such as state-space models, feedback control, and optimal control. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of modern control systems.
Provides a comprehensive introduction to robotics. It covers topics such as robot kinematics, dynamics, and control. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of robotics.
Provides a comprehensive introduction to computer vision. It covers topics such as image processing, feature detection, and object recognition. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of computer vision.
Provides a comprehensive introduction to machine learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of machine learning.
Provides a comprehensive introduction to deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of deep learning.
Provides a comprehensive introduction to reinforcement learning. It covers topics such as Markov decision processes, value functions, and policy gradients. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of reinforcement learning.
Provides a comprehensive introduction to automated reasoning. It covers topics such as logic, theorem proving, and automated planning. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of automated reasoning.
Provides a comprehensive introduction to knowledge representation and reasoning. It covers topics such as ontologies, logic programming, and defeasible reasoning. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of knowledge representation and reasoning.
Provides a comprehensive introduction to natural language processing. It covers topics such as part-of-speech tagging, parsing, and semantic analysis. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of natural language processing.
Provides a comprehensive overview of speech and language processing. It covers topics such as speech recognition, synthesis, and understanding. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of speech and language processing.
Provides a comprehensive introduction to information retrieval. It covers topics such as text processing, indexing, and retrieval models. It is an excellent resource for students and practitioners who want to learn more about the fundamentals of information retrieval.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/enw757/automated
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