- Machine Learning Fundamentals
- Apache Mahout Basics
- History of Mahout
- Supervised and Unsupervised Learning techniques
- Mahout and Hadoop
- Introduction to Clustering and Classification.
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Apache Mahout Training
Master the Apache Mahout concepts by joining the online training by Mindmajix.
Online
Quick facts
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekdays, Weekends
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Course overview
Apache Mahout Training course is online training offered by the online educational platform Mindmajix that is developed to enable the learners to understand the use of Apache Mahout. The curriculum will walk the participants through many aspects related to the Apache Mahout including Mahout on Apache Hadoop, Setting up Mahout and Myrrix, Clustering, K-means Canopy Clustering, and many more.
For the learners who plan to join the Apache Mahout Training online course, there are three modes available to pursue the programme i.e the self-paced e-learning videos, corporate training, and live instructor-led mode. The programme will equip the participants with the ability to do tasks in Apache Mahout, analyze the Big-data using tools, history of Mahout and set up Apache Mahout cluster, etc through many hands-on projects and practical examples. Mindmajix will also provide the candidates who completed the Apache Mahout Training certification the mock interview, access to the custom resume builder and self-paced videos, etc.
The highlights
- 100% online course
- Offered by Mindmajix
- Flexible Schedule
- Online Live and Self-paced Training Options
- FREE Demo on Request
- 24/7 Lifetime Support
- Life-Time Self-Paced Videos Access
- One-on-One Doubt Clearing
- Certification Oriented Curriculum
Program offerings
- One-on-one doubt clearing sessions
- Certification oriented curriculum
- Real-time project use cases
- 20 hours of labs
- Free demo on request
- 24/7 lifetime support
- 30 hours of sessions
- Online live and self-paced training options
Course and certificate fees
certificate availability
certificate providing authority
What you will learn
After the completion of the Apache Mahout Training online certification, the learners will be able to understand the concepts and tasks in Apache Mahout and machine learning. Plus, the students will develop a deep knowledge of Classification, Mahout on Amazon, EMR Mahout Vs R, Representing Data Feature Selection, Representing Vectors and whatnot.
Who it is for
The syllabus
Introduction To Machine Learning And Mahout
Apache Mahout And Hadoop
- Mahout on Apache Hadoop
- Setup Mahout and Myrrix.
Recommendation Engine In Mahout Training
- Recommendations using Apache Mahout
- Introduction to Recommendation systems
- Content Based Mahout Optimizations.
Implementing A Recommender And Recommendation Platform
- 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.
Clustering
- 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.
Classification
- Examples
- Basic Predictor variables and Target variables
- Common Algorithms
- SGD
- SVM
- Navie Bayes
- Random Forests
- Training and evaluating a Classifier
- Developing a Classifier
Apache Mahout And Amazon EMR
- Mahout on Amazon
- EMR Mahout Vs R
- Introduction to tools like Weka, Octave, Matlab and SAS
Project Included In Mahout Training
- 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.