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Workshop on Data Science

October 22, 2019

Many say the majority of data science work is getting the needed data right. To then maintain that data with quality over time to serve internal and external users while protecting your IP can be challenging. Especially at companies scaling fast!

During the AM session you will through a series of hands-on exercises practice how to ingest and govern access to data, and data refinery in place to serve data scientists and AI powered app development.

During the afternoon session you’ll, through a few exercises, learn how to go from problem to comparing approaches, train, deploy and test an ML model. You will also get an intro to do the same for an image recognition with a neural network model (aka deep learning).

This time we meet at our friends at Enfo, see location and read more about Enfo https://www.enfo.se

Completing this workshop you should understand how to:

  • Quickly ingest-, transform and integrate new data into usable assets
  • Work with existing data assets (discover, curate & categorize)
  • Govern data set- and analytical model sharing between individuals and teams under active policy management
  • Compare, choose and optimize a model for problem at hand
  • Manage models across training, evaluation and deployment
  • Deploy models as application services

This is a hands-on session and exercises will be done in Watson Studio on IBM Cloud, so please bring your laptop and get an account https://cloud.ibm.com/registration.

The workshop is led by Valerie Le Roy and Philippe Gregoire, data scientists at IBM Ecosystem advocacy hub. 

We will offer a limited number of seats for this workshop. Please manage your RSVP if you need cancel to give others the opportunity to join!

Look forward seeing you!