[Infographic] The Life of a Machine Learning Practitioner

Organizations are increasingly relying on machine learning (ML) algorithms to enhance business performance, innovate products, and improve customer experience, leading to a higher demand for ML practitioners in the United States. These professionals face various challenges in their work, including issues related to people, processes, and tools, which can slow down the development and deployment of ML models. A recent survey of 508 ML practitioners highlights that these challenges can create friction, making it difficult to track model training, collaborate effectively, and iterate quickly, ultimately delaying the deployment of models to production.

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