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Overview: Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to Machine Learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of Machine Learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement Machine Learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of Machine Learning quickly. Python and R are the two most highly used programming languages for developing ML programs. Python will be used as the only programming language in all examples of this book due to its ease of use, popularity, and the large, friendly, helpful, and interactive community Python encompasses. It is open-source, highly used in academic and research-based works, and is recommended by experts in almost every field. It is very efficient in terms of the amount of code needed to be written. The short, simple lines of Python code with obvious implications can be easily handled by beginners and are easy to read, debug, and expand. Python is also a cross-platform programming language, implying that it can run well on all operating systems and computers. The most used ML libraries are NumPy, Pandas, Scipy, Theano, Keras, Scikit-learn, Matplotlib, etc., while the most common frameworks are PyTorch and TensorFlow.
Genre: Non-Fiction > Tech & Devices
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