[Infographic] The Life of a Machine Learning Practitioner


Increasingly, organizations are relying on machine learning (ML) algorithms to optimize business performance, innovate products, and enhance customer experience. That means they’re increasingly hiring ML practitioners—individuals who develop and deploy algorithms and ML models—to apply the latest tools and techniques.

Who are these professionals, and what do they do? Here’s a glimpse into the life of a machine learning practitioner in the United States.

ML Practitioners Face Challenges

A recent survey shows ML practitioners are faced with challenges related to people, process, and tools. These challenges can create friction that makes it difficult to track model training runs and results, collaborate with colleagues, and iterate faster during the complex process of developing machine learning. This friction can cause delays in ML development that delay or halt model deployment to production.

Read the complete report on that independent survey of 508 ML practitioners, including data scientists and ML engineers.



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