Practical Machine Learning using Apache Spark and Big-Data


Machine learning based intelligent, predictive and smart systems are now part of every application domain and provide a major competitive advantage for many organizations. This session will introduce the Machine Learning in the field of software engineering and discuss various aspects of machine learning driven application development. I will cover the basics of supervised and unsupervised machine learning along with discussing its practical usage in the software industry. I will also introduce and use Apache Spark as distributed processing framework and it’s machine learning library (MLlib) to design and develop a practical application using machine learning algorithms during this session. Apache Spark is a big-data computing framework which is essential for any industry scale machine learning application that manages big data. No prior knowledge of machine learning or Apache Spark is required to attend this session.

Joy Chakraborty

Joy is a Distributed System Architect, 17+ yrs of Application Software development experience, 10+ yrs of .NET and C# development experience, 5+ yrs of work experience in ASP .NET web application scaling and performance improvement, 4+ yrs of WCF experience with a special interest in distributed/parallel computing, currently working on Cloud, Big Data and Machine Learning technologies for last 4+ years. Also, he is actively part of various Software architectural organization and active open source contributor on big-data projects.