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Build, Deploy and Monitor a Machine Learning Model on the Cloud

August 14, 2019  |  Webcast

In the not too distant past, Data Scientists worked in silos, doing their work on desktops and sharing Python and R scripts with their peers and external communities. Now, you have tools like Watson Studio and Jupyter Notebooks that make collaboration easier online.

While it is easy to share code with technical folks and dashboards with your non-technical friends, it is still hard to deploy your amazing models in a way that others can use it hassle free. Additionally, after you have deployed a model, you need to monitor it closely and re-deploy new improved models over time. This is the other learning over time in Machine Learning. Join IBM Developer SF in this hands-on workshop and successfully create, store and deploy a Machine Learning Model on IBM Cloud using Watson Studio and Watson Machine Learning Services within an hour. Don’t forget to bring your laptops !

Prerequisites – Curious minds ! Bring your laptop, and the rest happens on the cloud !

Who is this workshop for? Data Scientists who understand various model, hyper-parameters and are looking for ways to scare their model deployments and monitor/improve over time. Software developers who are looking to dip their feet into Machine Learning or want to create models to use in their applications. Data Science beginners who want to create their first model!

Speaker Bio:

Upkar Lidder is a Full Stack Developer and Data Wrangler with a decade of development experience in a variety of roles. He can be seen speaking at various conferences and participating in local tech groups and meetups. Upkar went to graduate school in Canada and currently resides in the United States