Machine learning (ML) is a powerful capability that can be incredibly difficult to implement in an enterprise environment. A full-featured data science platform, in concert with top-tier open-source tools, can serve as an effective machine learning operations (MLOps) platform to streamline the development and deployment of ML models. This combination of tools can empower practitioners to experiment, train models, and move solutions into production faster than ever before and dramatically reduce your time to value.
With our Enterprise Tier 5.7 release, Anaconda has added native, open-source MLFlow functionality. This update streamlines ML development, deployment, and model management to enable you to unlock the power of artificial intelligence (AI) for your organization.
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Director of Product Management, Anaconda
Chris has spent his career building and delivering technology products and solutions in the consumer and enterprise space. Most recently, he’s worked in product management, implementing machine learning solutions and building ML and data science platforms. Chris hails from Salt Lake City, Utah, where he can generally be found scampering around or skiing throughout the Wasatch Front.
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