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Optimizing an AI pipeline with Kubeflow

Photo of Florent Pietot
Hosted By
Florent P. and Edouard T.


<<< ⚠️ POSTPONED ⚠️ >>>
This event has to be postponed because of logistic issues consequences of the COVID-19 situation.
<<< --------------------- >>>

Nowadays we are getting in touch with different kinds of technologies. Especially the AI and Machine Learning market is growing with a velocity that has never been seen before. For all those different challenges we have to face in our daily business there is never this “one size fits it all” solution to everything. Hundreds of tools are available to help us in getting faster, better and more reliable. “Time spent” and “Go-To-Market”
is more important than ever before and therefore we need to optimize our processes and pipelines.

In this talk, we want to share our findings and experiences on building platform services for managing AI and ML-pipelines in an efficient manner. Using container-based technologies like Docker and Kubernetes we can improve the data scientists’ workflows without the need to know what happens in the background. It’s all about automation and self-service, whether it’s in the cloud or built as on-premises infrastructure. Managing data is also a very important yet often underestimated challenge to cover and talk about as this is the asset from which we generate the most value.

Kubeflow is one tool chest on which we focused our work and which we want to demo – showing an AI use case within its usual lifecycle compared to what gets possible when using the right tools at the right spot e.g. auto parameter fine-tuning and event-based workflow management alongside your own Jupyter notebook environment.

*** Agenda ***

  • Talk
  • Questions & Answers
  • Cocktail and networking

*** About the speaker ***
Working as an AI Solutions Architect – Data Scientist at NetApp, Muneer Ahmad Dedmari specialized in the development of Machine Learning and Deep Learning solutions. After working on various ML/DL projects industry-wide – he decided to dedicate himself to solutions in different hybrid cloud scenarios, in order to simplify the life of data scientists. He holds a Master’s Degree in Computer Science with a specialization in AI and Computer Vision from the Technical University of Munich.

*** About the sponsor ***
Algolia is a hosted search API that gives developers a complete toolkit for building search into their products. Our SaaS solution takes the pain out of building and maintaining search. We maintain the infrastructure and API clients for all important programming languages and platforms, and focus on the developer experience with extensive documentation, tooling and support.

*** Audience ***
This is a meetup for data professionals who want to push forward the productionization of machine learning development within their organizations: data scientists, data engineers, software and DevOps engineers, data project/product managers...

*** Contact ***
For any questions regarding the event or if you want to sponsor it, reach out to me at

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