Machine learning is a subfield of artificial intelligence that is concerned with the design, analysis, implementation, and applications of programs that learn from experience. It offers some of the most cost-effective approaches to automated knowledge acquisition in emerging data-rich disciplines (bioinformatics, cheminformatics, neuroinformatics, environmental informatics, social informatics, business informatics, security informatics, materials informatics, etc.). Learning algorithms can also be used to model aspects of human and animal learning.
Machine learning course is perfect for those who have a solid basis in R and statistics, but are complete beginners with machine learning. After a broad overview of the discipline's most common techniques and applications, you'll gain more insight into the assessment and training of different machine learning models. The rest of the course is dedicated to a first reconnaissance with three of the most basic machine learning tasks: classification, regression and clustering.
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