1 to marketing and winemaking. Xavier also links to his answer to '. What are the top 10 data mining or machine learning algorithms? Also you can get this book The Elements of Statistical Learning. I've created a handy mind map of 60 algorithms organized by type. optimization: How to use predictive models to optimize revenue, lap time or any other goal? Related: 5 Steps to Actually Learn Data Science 60 Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more. After reading this post you will know: About the classification and regression supervised learning problems. A problem that sits in between supervised and unsupervised learning called semi-supervised learning.
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If you are interested in any of the following topics please feel free to email me or to contact me on, linkedIn to explore a potential collaboration. Clustering : A clustering problem is where you want to discover the inherent groupings in the data, such as grouping customers by purchasing behavior. design of Experiments: If you have the chance to collect new data, what data will improve the predictive models the most? Get a grip on Statistics (academic discipline) and Probability. Download it, print it and use. Pdf bib, inteligencia Artificial para la vela, sail INN Pro, Bilbao, Essential Machine Learning, Course @ Carnovo, Barcelona, 20 December 2017.