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Organisational Challenges of MLOps

Posted May 08, 2021 | Views 661
# Data Science
# Machine Learning
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Adam Sroka
Director @ Hypercube Consulting

Dr. Adam Sroka, Director of Hypercube Consulting, is an experienced data and AI leader helping organizations unlock value from data by delivering enterprise-scale solutions and building high-performing data and analytics teams from the ground up. Adam shares his thoughts and ideas through public speaking, tech community events, on his blog, and in his podcast.

Many organizations aren't getting the most out of their data and many data professionals struggle to communicate their results or the complexity and value of their work in a way that business stakeholders can relate to. Being able to understand both the technology and how it translates to real benefits is key.

Simply hiring the most capable people often isn’t enough. The solution is a mix of clear and explicit communication, strong fundamentals and engineering discipline, and an appetite to experiment and iterate to success quickly.

If this is something you’re struggling with - either as an organization finding its feet with data and AI or as a data professional - the approaches and systems Adam has developed over his career will be able to help so please reach out.

Cutting-edge data technologies are redefining every industry and adopting these new ways of working can be difficult and frustrating. One day, there will be best practices and playbooks for how to maximize the value of your data and teams, but until then Adam is eager to share his experiences in both business and data and shed some light on what works.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Vishnu Rachakonda
Data Scientist @ Firsthand

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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SUMMARY

Deploying data science solutions into production is challenging for both small and large organizations. From platform and tooling wars to architecture and design pattern trade-offs it can get overwhelming for inexperienced teams. Furthermore, many organizations will only go through the painful discovery process once. Adam will share some of his experiences from consulting and leading data teams to successfully deploying machine learning solutions, highlighting some of the more difficult challenges to overcome. You might not be surprised to hear it’s not all down to the tech.

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