Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

Strong foundations in statistics and probability (at the undergraduate level), multivariate calculus and linear algebra, and good knowledge of a computer programming (C/C++, Python, etc). Interest in ...

Work you complete in the non-credit experience will transfer to the for-credit experience when you upgrade and pay tuition. See How It Works for details. A previous version of Machine Learning: Theory ...

Machine learning has been inducted into various domains for automation and insights. It has helped businesses grow by aiding decision-making based on data. Organizations create and deploy machine ...

I was pleased to receive a review copy of this new title from Cambridge University Press, “A Hands-on Introduction to Machine Learning.” The hardcover book is very attractive, well-produced and solid!

Machine learning allows a computer to teach itself how to solve problems by analyzing large sets of data. Human programmers don't teach machine learning systems how to solve problems, nor do they ...

Machine learning may sound relatively old-fashioned in the age of AI, but it remains a valuable and oft-used skill. Machine learning is the use of algorithms in computer systems to “learn” from data, ...

How much math knowledge do you need for machine learning and deep learning? Some people say not much. Others say a lot. Both are correct, depending on what you want to achieve. There are plenty of ...