Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI.
About this Course
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Learner Career Outcomes
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
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TOP REVIEWS FROM MACHINE LEARNING
Great explanation of each topic. However i felt the course is little outdated and it would have been better if it has topics related to python/R algorithm class libraries and algorithm implementation.
This is the best course I have ever taken. Andrew is a very good teacher and he makes even the most difficult things understandable. A big thank you for spending so many hours creating this course.
Very good teaching.. Very valuable learning.. Course is Worth every penny. A little too intense timeline for people working fulltime. It would be even more beneficial if it was taught using python.
Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.
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