Machine Learning with Mahout
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Updated On 02 Feb, 19
Apache Mahout Tutorial - Machine Learning with Mahout - Introduction to Apache Mahout - What is Mahout ? - Mahout Overview - Machine Learning Use cases - Classification of Apache Mahout - Mahout Machine Learning - Learning Techniques in Mahout - Supervised Learning Technique In Mahout - Introduction to Recommendation Systems - Introduction to Pearsons Correlation - Understanding Distance Measures in Apache Mahout - Understanding Euclidean Distance & Cosine Similarities in Mahout - Tanimoto Coefficient - Understanding Basics of Clustering - Introduction to Clustering in Mahout - Clustering Algorithms - ClickStream Analytics in Mahout - Introduction to Fuzzy K Means - Collaborative Filtering Framework - Similarities Metrics in Mahout - Introduction to Myrrix and Oryx - What is Canopy Clustering | Canopy Clustering in Mahout - What is Topic Model | Understanding LDA (Latent Dirichlet Allocation) - Introduction to Clustering Techniques - Understanding Apriori Algorithm - Apriori Algorithm Using Mahout - Mahout Clustering - Mahout Clustering Tutorial - Apache Mahout Clustering - Mahout Overview - Mahout Machine Learning - Mahout Use Cases - Apache Mahout Tutorial
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The Tanimoto coefficient is the ratio of the size of the interaction, or overlap, in two users’ preferred items, to the union of the users’ preferred items (the dark and light areas together). Watch the video to have a better understanding of the concept.
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The topics related to ‘Tanimoto Coefficient’ have extensively been covered in our course ‘Apache Mahout’.
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Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
March 29, 2019
Great course. Thank you very much.