Predictive & Advanced Analytics
29 - 30 May 2018
Van der Valk Hotel Utrecht, The Netherlands
Look at how machine learning and advanced analytical techniques techniques such as text analyses, sentiment analysis, graph and streaming analytics can be used at scale on Big data to provide new insight that helps foster growth, reduce costs and improve effectiveness for competitive advantage.
This new 2-day seminar looks at the need to capture new data sources to add to what we already know and use machine learning to automatically discover, profile and catalog what is in these data sources. It then looks at how machine learning and advanced analytical techniques such as text analyses, sentiment analysis, graph and streaming analytics can be used at scale on Big data to provide new insight that helps foster growth, reduce costs and improve effectiveness for competitive advantage.
Learning objectives
- How data and analytical characteristics can dictate the approach taken and tools needed to conduct exploratory analytics
- How to develop analytical models using supervised and unsupervised machine learning
- How to develop machine learning models at scale on Apache Spark and Hadoop
- Tools for building machine learning models
- Tools and techniques for discovery, analysis and visualisation of multi-structured data
- Text and sentiment analysis
- Scaling text analysis to run on Hadoop, MapReduce and Spark
- Clickstream analysis
- Graph analysis – 4 graph analytical techniques to identify shortest path, analyse connectivity, identify communities, determine influencers and important people in social networks etc.
- Scale graph analysis on Apache Spark GraphX
- Analyse fast data in real-time using streaming analytics
- Leverage machine learning and advanced analytics quickly and easily from self-service BI reports and dashboards for access over the web and on mobile device.
Enter your details to participate in the webinar.
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