Getting a machine learning solution in front of users usually takes some time. The data science tech stack is full of time traps and infrastructure issues might slow down deployment. The Azure Machine Learning platform, automated machine learning, and Streamlit are predestined tools for circumventing common development and deployment issues – if you know how to use them. Based on our learnings in corporate hackathons, we will use the stack to rapidly prototype a computer vision application users can interact with. You will walk away with Python code snippets and inspiration to build and user test your own machine learning ideas quickly.

Florian Roscheck

Affiliation: Henkel AG & Co. KGaA

Florian is a Sr. Data Scientist at Henkel where he develops machine learning solutions for R&D and production use cases across the company's adhesive and consumer good portfolios. He is also known as online instructor for the open-source data engineering framework Apache Spark. Florian volunteers his time as the current Vice President of the Affiliated Project Selection Committee at NumFOCUS, helping scientific open-source projects grow.

visit the speaker at: Github