MATLAB and Python are the two powerhouse languages for engineers, scientists, and data analysts, essential for numerical computing, simulation, and analysis. MATLAB is highly used to tackle scenarios such as signal processing, thermal simulations, structural analysis, modeling of mathematical systems, etc. On the other hand, Python has its own demand in different fields, such as data analysis, data visualization, machine learning, statistical modeling, classification models, regression models, quantitative analysis, etc.

This book develops an understanding of how MATLAB and Python can be used in parallel ways to deal with coding problems. A deep understanding of several concepts is provided via MATLAB and Python, such as variables and data types, basic operations, control flow and structures, functions, data handling, plotting and visualization, signal processing, image processing, etc. With the help of several hands-on examples, readers will be able to gain practical insights and will also be able to tackle real-life problems.

By the end of this book, readers will be able to have confidence to code in MATLAB and Python, along with an understanding of the strengths of each tool. This book will give readers the ability to write efficient code, how to do data analysis, how to create visualizations, and how to deal with signal and image processing in an easy and efficient way.

What you will learn

● Gain full insights about data handling and data visualization in MATLAB and Python.

● Knowledge about signal and image processing in MATLAB and Python.

● Apply coding skills to solve real-world problems.

● Selection of right language for specific coding tasks.

● Compare matrices, lists, tuples, and cell arrays.

● Execute matrix operations and advanced string handling.

● Implement conditional logic and iterative loop structures.

● Implement signal and image processing with OpenCV and libraries.

Who this book is for

This book is ideal for engineering students, researchers, scientists, and data analysts with foundational programming knowledge who aim to efficiently transition or compare skills across MATLAB and Python for scientific computing.

Table of Contents

1. Introduction to MATLAB and Python

2. MATLAB and Python Variables and Data Types

3. Basic Operations in MATLAB and Python Languages

4. Control Flow and Structures in MATLAB and Python

5. Functions and Scripts in MATLAB and Python

6. Data Handling in MATLAB

7. Data Handling in MATLAB and Python

8. Plotting and Visualization in MATLAB

9. Plotting and Visualization in Python

10. Working with Data in MATLAB and Python

11. Signal and Image Processing in MATLAB and Python

12. Case Studies in MATLAB and Python

About the Author

Dr. Mamta Kapoor is a mathematician and researcher. Her research areas are numerical approximation of linear and non-linear partial differential equations, semi-analytical solution of fractional partial differential equations, fractional calculus, fuzzy calculus, scientific computing, numerical analysis, and fluid mechanics.

"About this title" may belong to another edition of this title.

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