Natalino is Head of Data Science at Teradata, where he provides consultancy services and delivers big/fast data solutions for data-driven applications such as predictive analytics, personalized marketing, man-machine interaction, fraud and cyber security. O’Reilly author and advocate of Open Source Software, and the Apache Software Foundation. Polyglot Jupyter Notebooks programmer and passionate about distributed processing projects such as Spark, Cassandra, Kafka, Akka, Tensorflow, Mesos.
Previously, served as Enterprise Data Architect at ING in the Netherlands. Before that, he has served as senior researcher at Philips Research Laboratories in the Netherlands, on the topics of system-on-a-chip architectures, distributed computing and compilers. All-round Technology Manager, Product Developer, and Innovator with 15+ years track record in research, development and management of distributed architectures and scalable services and applications. Blogs regularly about big data, analytics, data science and scala reactive programming at natalinobusa.com
Natalino is going to present about the latest advances in machine learning algorithms, big data tools and cloud engineering practices.
Are we reaching a Data Science Singularity?
How Cognitive Computing is emerging from Machine Learning Algorithms, Big Data Tools, and Cloud Services
Prescriptive analytics is the ultimate analytical step which goes beyond predictions into the realm of goal-oriented recommendations. As such, we could consider prescriptive analytics as a particular sort of cognitive computing. In 2016, how far are we from cognitive computing actually? Will Cognitive Computing emerge from Machine Learning Algorithms, Big Data Tools, and Cloud Services?
In this talk, Natalino will describe the latest advances in machine learning algorithms, big data tools and cloud engineering practices. These are the ingredients which are blended together to brew modern AI, prescriptive analytics and cognitive processing solutions. As data, and algorithms are made available into large cloud computing clusters, higher-level, cognitive-like services will solve real-world, complex and often ambiguous cases.