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Description

About Apache Mahout Apache Mahout is a project of the Apache Software Foundation which is implemented on top of Apache Hadoop and uses the MapReduce paradigm.  It is also used to create implementations of scalable and distributed machine learning algorithms that are focused in the areas of clustering, collaborative filtering and classification. Mahout contains Java libraries for common math algorithms and operations focused on statistics and linear algebra, as well as primitive Java collections.  An aspirant can learn more from Apache Mahout training which covers all the topics from basics to advanced level. Course  Apache Mahout Training Mode of Training  Instructor Led Live Online Training Duration  30 hours Timings  Flexible (Our Rep will work with you on the timings that suits your needs) Course Material  Our Expert Trainer will share you all the necessary course material,  ppt's, videos and pdf's Examples  Trainer will cover Real time scenarios during the training Interview Questions  Click here to see the Interview Questions Salary Trends  Check here to see the salary trends here. Why to attend Tekslate Online Training ?? Classes are conducted by Certified Apache Mahout Working Professionals with 100 % Quality Assurance. With an experienced Certified practitioner who will teach you the essentials you need to know to kick-start your career on Apache Mahout. Our training make you more productive with your Apache Mahout Online Training. Our training style is entirely hands-on. We will provide access to our desktop screen and will be actively conducting hands-on labs with real-time projects. Who should attend Apache Mahout training? The following people can be attend Apache Mahout. Analytics Professionals Data Scientists looking to hone their machine learning skills Software Developers and Architects Business Analysts wanting to learn Mahout for ML implementation Professionals working with R, Matlab, Python, etc. Statisticians looking to learn machine learning techniques Graduates aspiring to take a leap in analytics domain Prerequisites Learning Apache Mahout course doesn’t need any specific prerequisites as such but basic knowledge on Java and Hadoop concepts would be advantageous. Apache Mahout training objectives After the completion of the Apache Mahout Training, a participant will be able to Gain an insight into the Machine Learning techniques. Understand the algorithms of SVM, Naive Bayes, Random Forests,etc. Implement these using 'Apache Mahout' Understand the recommendation system Learn Collaborative filtering, Clustering and Categorization Analyse Big Data using Hadoop and Mahout Implementing a recommender using MapReduce Introduction to tools like Weka, Octave, Matlab, SAS Apache Mahout Training Curriculum Introduction to Machine Learning and Mahout Machine Learning Fundamentals, Apache Mahout Basics, History of Mahout, Supervised and Unsupervised Learning techniques, Mahout and Hadoop, Introduction to Clustering and Classification 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 A complete recommendation engine built on application logs and transactions Apache Mahout Certification After the completion of Apache Mahout training, it would be a priority point for a trainee to acquire Apache Mahout Certification as the corporate world accepts profile that is arrayed with Apache Mahout certification. Benefits of being certified in Apache Mahout technology would be: Distinguished as an expert in the IT market. Racing in low competition area in the Apache Mahout platform. Remunerated with an uncommon package. To achieve Certification in Apache Mahout technology, you need to visit the following site: https://mapr.com/blog/ecosystem-certification-for-mahout-hive-and-oozie/ Benefits to our Global Learners Tekslate is trainee-focused Quality training delivered with comparatively low fee structure across the globe Lifetime Access to recorded video sessions of the training classes Exposure on real-time scenarios in varied domains by industry experts Salary Trends Average Apache Mahout Salary in USA is increasing and is much better than other products. Ref: Indeed.com

Key Features

  • 30 hours of Instructor Led Apache Mahout Training
  • Lifetime Access to Recorded Sessions
  • Practical Approach
  • 24/7 Support
  • Expert & Certified Trainers
  • Real World use cases and Scenarios
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