Data Science Learnathon: From Raw Data to Deployment, Dallas

At KNIME®, we build software for fast, easy and intuitive access to advanced data science, helping organizations drive innovation.Our KNIME Analytics Platform is the leading open solution for data-driven innovation, designed for discovering the potential hidden in data, mining for fresh insights, or predicting new futures.Organizations can take their collaboration, productivity and performance to the next level with a robust range of commercial extensions to our open source platform.For over a decade, a thriving community of data scientists in over 60 countries has been working with our platform on every kind of data: from numbers to images, molecules to humans, signals to complex networks, and simple statistics to big data analytics.KNIME’s headquarters are based in Zurich, with additional offices in Konstanz, Berlin, and Austin. We’re open for innovation®, so visit us atKNIME.com.

KNIME

This data science learnathon covers the entire data science cycle and gives participants the chance to work together on guided exercises.
What is a learnathon? It's between a hackathon and a workshop. It's like a workshop because we'll learn more about the data science cycle - data access, data blending, data preparation, model training, optimization, testing, and deployment. It's like a hackathon because we'll work in groups to hack a workflow-based solution to guided exercises. The tool of choice for this learnathon is <A HREF="https://www.knime.com/knime-analytics-platform" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">KNIME Analytics Platform</A>. 
KNIME Analytics Platform is an open, open-source, GUI driven, data analytics platform, that covers all your data needs from data import to final deployment. Being open, KNIME Analytics Platform offers a vast integration and IDE environment for R, Python, SQL, and Spark.
After an initial introduction to the tool and to the data science cycle, we will split in groups. Each group will focus on one of three aspects of the data science cycle:
<UL>
<LI>Group 1. Working on the raw data. Data access and data preparation.</LI>
<LI>Group 2. Machine Learning. Which model shall I use? Which parameters?</LI>
<LI>Group 3. I have a great model. Now what? The model deployment phase.</LI>
</UL>
We will provide a few datasets, jump-start workflows and final solutions for the proposed tasks, and of course data science experts. Please bring your own laptop with KNIME Analytics Platform pre-installed. To install KNIME Analytics Platform, follow the instructions provided in these YouTube videos:
<UL>
<LI><A HREF="https://www.youtube.com/watch?v=yeHblDxakLk&feature=youtu.be" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Windows</A></LI>
<LI><A HREF="https://www.youtube.com/watch?v=1jvRWryJ220&feature=youtu.be" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Mac</A></LI>
<LI><A HREF="https://www.youtube.com/watch?v=wibggQYr4ZA&feature=youtu.be" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Linux</A></LI>
</UL>
If you would like to get familiar with KNIME Analytics Platform, you can explore the content of our <A HREF="https://www.knime.com/knime-introductory-course" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">E-learning course</A>.
Please also download the workshop material (jump-start workflows and instructions) from <A HREF="https://www.dropbox.com/s/n7kkr4intau7f1b/Learnathon_2019.knar?dl=0" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">here</A>. We will import this material during the learnathon.
<H2>Agenda</H2>
<UL>
<LI>6:00 PM - Reception</LI>
<LI>6:15 PM - Welcome</LI>
<LI>6:30 PM - Introduction to KNIME Analytics Platform</LI>
<LI>6:50 PM - The Data Science Cycle: From Raw Data to Deployment</LI>
<LI>7:10 PM - Let's Work and Learn!</LI>
<LI>9:15 PM - Networking</LI>
</UL>

3010 LBJ

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Data Science Learnathon: From Raw Data to Deployment, Dallas

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Data Science Learnathon: From Raw Data to Deployment, Dallas

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