MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and built-in functions to easily exploit MATLAB’s extensive capabilities for tackling engineering and scientific problems. Assumin
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MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and built-in functions to easily exploit MATLAB’s extensive capabilities for tackling engineering and scientific problems. Assumin
MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and built-in functions to easily exploit MATLAB’s extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. The sixth edition has been updated to reflect the functionality of the current version of MATLAB (R2021a), including the introduction of machine learning concepts and the Machine Learning Toolbox, and new sections on data formats and data scrubbing.
- Presents programming concepts and MATLAB built-in functions side by side, giving students the ability to program efficiently and exploit the power of MATLAB to solve technical problems
- Offers sections on common pitfalls and programming guidelines that direct students to best practice procedures
- Tests conceptual understanding of the material with Quick Questions! and Practice sections within each chapter
- Full color treatment of charts, graphs, grids and special chapter sections such as Quick Questions and Key Terms enhances readability and learning of MATLAB programming concepts and functions
- Content in this edition has been updated to MATLAB version R2021a where appropriate
- For this edition, new sections introducing concepts relevant to machine learning have been added to the end of every chapter along with a new Introduction to Machine Learning chapter
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