During the last few years, machine learning has moved to centre stage in the world of technology. Today, thousands of engineers and researchers are applying machine learning to an extraordinarily broad range of domains. However, making effective use of machine learning in practice can be daunting, especially for newcomers to the field. When someone is trying to solve a real-world problem using machine learning, they often encounter challenges.
In this book we look at machine learning from a fresh perspective which we call model-based machine learning. Model-based machine learning helps to address all of these challenges, and makes the process of creating effective machine learning solutions much more transparent.
John Winn with Christopher M. Bishop, Thomas Diethe, John Guiver and Yordan Zaykov
The techniques and tools covered in Model-Based Machine Learning are most similar to the requirements found in Data Scientist job advertisements.
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