Brief | Book | |
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This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
I have several machine learning books, and most of them are more in depth, but lacking a broader overview of machine learning. So if you want an overview of different problem solving techniques, this is the book for you. It has enough theory to keep most people happy. If you want to know the core motivational aspect to the finest details, this book will be lacking in some areas. Other books may have more detail, but just know they won't cover as much of the overall subject. This is always my go to book for trying to remember something. It's small, light, and enough to get me back on track. I have other books for more in depth reading, but they don't cover as much of the subject of machine learning as this one. |
Why? - build a strategic, smart and strong analytics capability to transform your institution and ensure a future proof competitive advantage. This type of transformation impacts top-line growth—such as those related to institutional transformation and data utilization—as well as productivity and performance. This discipline includes: Agile and rapid prototyping. Analytics capability assessment and transformation. Remember the conviction: #Analyticship:#BI,#ML,#AI,#BigData,#Analytics,#HiEd:
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Tuesday, August 11, 2020
Machine Learning...Computer Science Series
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