Machine Learning with Mahout

Overview 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

Beginner 0(0 Ratings) 1 Students enrolled English
Created by skill expert
Last updated Mon, 13-Jun-2022
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Course overview
Lecture Details

Watch the sample class recording httpwww.edureka.comahout?utm_source=youtube&utm_medium=referral&utm_campaign=mahout-tutorial-1

Apache mahout is known to produce free impelementations of distributed or otherwise scalable machine learning algorithms focussed primarily in the areas of clustering and classification.

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Some of the topics covered in this video are as follows
1. Introduction to Machine Learning and Apache mahout
2. Mahout and Hadoop
3. Recommendation Engine
4. Impelementing a recommender and recommendation platform
5. Clustering
6. Classification
7. Mahout and Amazon EMR
8. Project Discussion

Curriculum for this course
28 Lessons 13:36:14 Hours
Lecture
28 Lessons 13:36:14 Hours
  • Apache Mahout Tutorial-1
    Preview 01:13:40
  • Apache Mahout Tutorial-2
    02:07:50
  • Machine Learning with Mahout
    00:34:35
  • Introduction to Apache Mahout
    00:28:40
  • What is Mahout ?
    00:25:41
  • Classification of Apache Mahout
    01:23:21
  • Mahout Machine Learning
    00:06:53
  • Learning Techniques in Mahout
    00:19:57
  • Supervised Learning Technique In Mahout
    00:11:06
  • Introduction to Recommendation Systems
    00:45:56
  • Introduction to Pearsons Correlation
    00:16:32
  • Understanding Distance Measures in Apache Mahout
    00:07:08
  • Understanding Euclidean Distance & Cosine Similarities in Mahout
    00:04:09
  • Tanimoto Coefficient
    00:04:24
  • Understanding Basics of Clustering
    00:19:15
  • Clustering Algorithms
    00:13:13
  • ClickStream Analytics in Mahout
    00:04:25
  • Introduction to Fuzzy K Means
    00:04:35
  • Collaborative Filtering Framework
    00:20:55
  • Similarities Metrics in Mahout
    00:19:32
  • Introduction to Myrrix and Oryx
    00:08:32
  • What is Canopy Clustering | Canopy Clustering in Mahout
    00:36:07
  • What is Topic Model-Understanding LDA
    00:26:58
  • Introduction to Clustering Techniques
    00:20:08
  • Understanding Apriori Algorithm-Apriori Algorithm Using Mahout
    00:35:41
  • Mahout Clustering Tutorial-Apache Mahout Clustering
    01:00:44
  • Mahout Overview-Mahout Machine Learning
    00:30:41
  • Mahout Use Cases-Apache Mahout Tutorial
    00:25:36
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