So, first time about Mahout at Jacksonville- I am introducing this seminar in anticipation with booming nature of Analytics domain and huge volumes of data collected by the organizations in various formats. To generate valuable information and to make a managerial decision from these large chunks of data, organizations have started using powerful tools and software which in turn help them increase their revenues. Mahout is one such tool/Apache project which uses library of algorithms for large scale text documents, classify and organize them into groups of technically related documents; and generate results that are valuable to the organizations. ‘Mahout’ by HUGNOFA caters to a wide range of audiences including the Data Analyts, Java Programmers, Hadoop Developers/Administrators/Architect and anyone who aspires to seek a career in Big Data domain.
I will kick start by familiarizing the learners with fundamental knowledge of Machine Learning techniques like Clustering, Collaborative Filtering, and Classification; and would also explain where Mahout fits in. After learner’s acquaintance with Machine Learning techniques, I will give an in-depth understanding of concepts like recommendation systems, their types, how to choose a similarity algorithm, typical design of a recommendation system; and clustering and classification. Also, learners will be exploring many examples of recommendations. I will also introduce decision trees and will showcase how you will use it for predictive analysis. And of course , at the end , you will know what entropy is, and what information gain is.
Please reserve asap as library has a limited capacity. We have allowed only first 35. Sorry for the inconvenience.