Next Meetup + KNIME Joint Event: Sparkling Water Special Edition!
Many thanks to Rob Slater from CognitiveCredit, we have a great venue for our first meetup in 2019. Agenda: - Doors open at 6pm. Pizzas + Drinks + Networking - Welcoming Remarks ( & CognitiveCredit) - Talk 1: What's New in H2O-3 & Sparkling Water by team - Talk 2: Leveraging H2O with KNIME by Paolo Tamagnini ===== Talk 1: What's New in H2O-3 & Sparkling Water? The H2O team is in town. We would like to invite you to join us on Jan 23rd for our London meetup. We will show you some new features in our open-source machine learning platforms H2O-3 and Sparkling Water. In our latest release (3.22), we implemented new functions like isolation forest, tree inspection API, and target encoding. Come and find out more :) About team: Jakub Háva ( Václav Belák ( Pavel Pscheidl ( Jo-fai Chow ( ===== Talk 2: Leveraging H2O Machine Learning with KNIME Analytics Platform KNIME Analytics Platform is the open source software for creating data science applications and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. Open source integrations for KNIME Analytics Platform, provide seamless access to large open source projects - including a variety of different machine learning libraries. For example you can use from KNIME large open source projects such as Keras and Tensorflow for deep learning, Apache Spark for big data processing, Python and R for scripting, and more. The integration of H2O in KNIME offers an extensive number of nodes, all encapsulating functionalities of the H2O open source machine learning libraries. This makes it easy to use H2O algorithms from a KNIME workflow without touching any code while benefiting from the high performance libraries and proven quality of H2O during execution. For prototyping, these algorithms are executed locally, however training and deployment can easily be scaled up using a Sparkling Water cluster. In our talk we’ll give a short introduction to KNIME Analytics Platform and then demonstrate how data scientists benefit from using KNIME Analytics Platform and H2O Machine Learning together. We’ll do this by showing a real world analysis example. About Paolo: Paolo Tamagnini, currently works as a data scientist at KNIME. Paolo holds a master’s degree in Data Science from Sapienza University of Rome and has research experience in data visualization for machine learning interpretability from working and studying at New York University.


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    Welcome to the group. We’re excited to bring you the latest happenings in AI, Machine Learning, Deep Learning, Data Science and Big Data.

    Who are we? We’re (, creators of the world’s leading open source deep learning and machine learning platform, used by more than 140,000 data scientists and 14,000 organizations around the world.

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