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Learn how to use Apache Mahout. Mindmajix Apache Mahout training helps you to learn tasks in Apache Mahout, Learning Tools for use on analyzing Big-data, how to setup Apache mahout cluster, History of Mahout…etc.
Course Coverage
You will be exposed to the complete Apache Mahout Trainingcourse details in the below sections.
In Mahout Training, you will know what is machine learning, what is Apache mahout and what is clustering.
Machine Learning Fundamentals
Apache Mahout Basics
History of Mahout
Supervised and Unsupervised Learning techniques
Mahout and Hadoop
Introduction to Clustering and Classification.
Myrrix is a recommendation engine based on mahout, therefore this module is designed for mahout training and myrrix.
Mahout on Apache Hadoop
Setup Mahout and Myrrix.
This module will focus on Recommendation algorithm and Mahout optimizations.
Recommendations using Apache Mahout
Introduction to Recommendation systems
Content Based Mahout Optimizations.
Understanding the various recommendations, implementing Recommendors, different types of similarities in Apache mahout.
User based recommendation
User Neighbourhood
Item based Recommendation
Implementing a Recommender using MapReduce Platforms
Similarity Measures
Manhattan Distance
Euclidean Distance
Cosine Similarity
Pearson’s Correlation Similarity
Log likelihood Similarity
Tanimoto Evaluating
Recommendation Engines (Online and Offline)
Recommendors in Production.
This module is designed to give you thoroughly over the clustering concepts.
Clustering
Common Clustering Algorithms in Apache mahout training
K-means Canopy Clustering
Fuzzy K-means and Mean Shift etc.
Representing Data Feature Selection
Vectorization in Apache Mahout training
Representing Vectors
Clustering documents through example TF-IDF and Implementing clustering in Hadoop Classification.
By the end of this training module, you will be able to develop a classifier on your own.
Examples
Basic Predictor variables and Target variables
Common Algorithms
SGD
SVM
Navie Bayes
Random Forests
Training and evaluating a Classifier
Developing a Classifier
We’ll focus on Apache Mahout and Amazon EMR, have an overview on Weka, Octave Matlab and SAS.
Mahout on Amazon
EMR Mahout Vs R
Introduction to tools like Weka, Octave, Matlab and SAS
This is the implementation module, of what we have learnt so far in Apache Mahout training.
A complete recommendation engine is built on application logs and transactions.
Our Apache Mahout Training course aims to deliver quality training that covers solid fundamental knowledge on core concepts with a practical approach. Such exposure to the current industry use-cases and scenarios will help learners scale up their skills and perform real-time projects with the best practices.
Passing Apache Mahout Quizzes & Assessment exams is mandatory to attain the Apache Mahout Course Completion certificate
Training OptionsBoth options cover the full curriculum and include most of the certification topics
Learn anytime, at your own pace — complete the course in weeks or months.
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We believe in transparency. Here's how MindMajix stacks up against typical Apache Mahout training providers so you can compare value, support, and practical depth clearly.
Apache Mahout Training
5164 learnersGeneric Apache Mahout Training Providers
Updated to the latest exam pattern with real-world modules, guided labs, and implementation depth.
Always currentOften outdated basics with limited real-world coverage and shallow practical context.
Frequently outdatedSandbox-style practice with guided exercises, projects, and replay-friendly learning support included.
Included at no extra costSlides-first teaching with restricted lab time or paid add-on practical access.
Limited / paid extraCertified trainers with real implementation experience and structured teaching support.
Verified expertiseTrainer quality varies widely and may depend on availability rather than specialization.
Varies widelyA stable trainer journey with consistent delivery, doubt support, and batch continuity.
Consistent trainerTrainer substitutions can happen mid-course and interrupt learning continuity.
Frequent changesOngoing help through trainer sessions, community support, and guided clarification after class.
Extended supportSupport often stops after sessions, leaving little structured post-class help.
No post-training helpResume reviews, mock interviews, hiring guidance, and practical interview preparation support.
Active placement supportPlacement support is often limited to generic guidance or an email list.
Mostly nominalStructured mock interview rounds with domain-focused feedback before interviews.
IncludedStudents are usually expected to prepare independently without guided mock rounds.
Not includedWeekday, weekend, and flexible learning paths with guidance on the best fit.
Fully flexibleFixed schedules with fewer alternatives once a batch begins.
Limited optionsPractice questions, revision guidance, and exam-focused preparation aligned to current objectives.
Comprehensive prepGeneric question banks that may not reflect the latest exam priorities.
Outdated mock testsStrong value with training, support, and practical learning included as a single package.
Best value for inclusionsLower headline pricing can still lead to add-on costs for labs, support, or extras.
Hidden add-on costsLong-term access to recordings and study materials for revision after batch completion.
Lifetime-style accessAccess is often time-limited and may not include refreshed supporting material.
Time-limited accessUpdated to the latest exam pattern with real-world modules, guided labs, and implementation depth.
Always currentOften outdated basics with limited real-world coverage and shallow practical context.
Frequently outdatedSandbox-style practice with guided exercises, projects, and replay-friendly learning support included.
Included at no extra costSlides-first teaching with restricted lab time or paid add-on practical access.
Limited / paid extraCertified trainers with real implementation experience and structured teaching support.
Verified expertiseTrainer quality varies widely and may depend on availability rather than specialization.
Varies widelyA stable trainer journey with consistent delivery, doubt support, and batch continuity.
Consistent trainerTrainer substitutions can happen mid-course and interrupt learning continuity.
Frequent changesOngoing help through trainer sessions, community support, and guided clarification after class.
Extended supportSupport often stops after sessions, leaving little structured post-class help.
No post-training helpResume reviews, mock interviews, hiring guidance, and practical interview preparation support.
Active placement supportPlacement support is often limited to generic guidance or an email list.
Mostly nominalStructured mock interview rounds with domain-focused feedback before interviews.
IncludedStudents are usually expected to prepare independently without guided mock rounds.
Not includedWeekday, weekend, and flexible learning paths with guidance on the best fit.
Fully flexibleFixed schedules with fewer alternatives once a batch begins.
Limited optionsPractice questions, revision guidance, and exam-focused preparation aligned to current objectives.
Comprehensive prepGeneric question banks that may not reflect the latest exam priorities.
Outdated mock testsStrong value with training, support, and practical learning included as a single package.
Best value for inclusionsLower headline pricing can still lead to add-on costs for labs, support, or extras.
Hidden add-on costsLong-term access to recordings and study materials for revision after batch completion.
Lifetime-style accessAccess is often time-limited and may not include refreshed supporting material.
Time-limited accessIndustry-focused delivery with stronger support, consistency, and practical learning value.
Lower upfront pricing can hide trade-offs in labs, trainer continuity, and support quality.
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