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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Course Curriculum

Apache Mahout Tutorial-1 Details 1:13:41
Apache Mahout Tutorial-2 Details 2:7:51
Machine Learning with Mahout Details 34:35
Introduction to Apache Mahout Details 28:41
What is Mahout ? Details 25:41
Mahout Overview Details 8:55
Machine Learning Use cases Details 8:54
Classification of Apache Mahout Details 1:23:23
Mahout Machine Learning Details 6:54
Learning Techniques in Mahout Details 19:58
Supervised Learning Technique In Mahout Details 11:7
Introduction to Recommendation Systems Details 45:57
Introduction to Pearsons Correlation Details 16:33
Understanding Distance Measures in Apache Mahout Details 7:9
Understanding Euclidean Distance & Cosine Similarities in Mahout Details 4:10
Tanimoto Coefficient Details 4:25
Understanding Basics of Clustering Details 19:16
Introduction to Clustering in Mahout Details 2:46
Clustering Algorithms Details 13:14
ClickStream Analytics in Mahout Details 4:26
Introduction to Fuzzy K Means Details 4:35
Collaborative Filtering Framework Details 20:56
Similarities Metrics in Mahout Details 19:33
Introduction to Myrrix and Oryx Details 8:33
What is Canopy Clustering | Canopy Clustering in Mahout Details 36:8
What is Topic Model | Understanding LDA (Latent Dirichlet Allocation) Details 26:58
Introduction to Clustering Techniques Details 20:9
Understanding Apriori Algorithm | Apriori Algorithm Using Mahout Details 35:42
Mahout Clustering | Mahout Clustering Tutorial | Apache Mahout Clustering Details 1:45
Mahout Overview | Mahout Machine Learning Details 30:41
Mahout Use Cases | Apache Mahout Tutorial Details 25:37

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