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Machine Learning with Mahout

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Updated On 02 Feb, 19

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

Includes

Lecture 29: Mahout Clustering | Mahout Clustering Tutorial | Apache Mahout Clustering

4.1 ( 11 )


Lecture Details

Watch Sample Class Recording httpwww.edureka.comahout?utm_source=youtube&utm_medium=referral&utm_campaign=clustering-tech-new

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar
(in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique
for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.

Know More about various clustering techniques through this video.

Following are the topics covered in the video

1.Difference between various clustering techniques.

2. K- means Clustering

3.Fuzzy K- means Clustering

4.Fuzzy K- means Clustering mapreduce flow.

5.Various clustering algorithms.


Related Blogs
httpwww.edureka.coblogintroduction-to-clustering-in-mahout?utm_source=youtube&utm_medium=referral&utm_campaign=clustering-tech-new

httpwww.edureka.coblogk-means-clustering?utm_source=youtube&utm_medium=referral&utm_campaign=clustering-tech-new


Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning
environment, accessible from any part of the world.

The topics related to ‘Clustering Techniques’ have extensively been covered in our course ‘Machine Learning with Mahout’.
For more information, please write back to us at sales@edureka.co
Call us at US 1800 275 9730 (toll free) or India +91-8880862004

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Comments
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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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