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Key Considerations for Optimal Machine Learning Deployments


Machine learning (ML) is being used almost everywhere, but the ubiquity has not been equated with simplicity. If you solely consider the operationalization aspect of ML, you know that deploying your models into production, especially in real-time environments, can be inefficient and time-consuming. Common approaches may not perform and scale to the levels needed. These challenges are especially true for businesses that have not properly planned out their data science initiatives.

In this webinar, Forrester VP and Principal Analyst Mike Gualtieri will share his research on the challenges that businesses face around ML inferencing in production. Mike will then lead a discussion with technology experts John DesJardins of Hazelcast around what data science and IT teams should consider to optimize the outcomes of their ML strategies.

Also, check out 5 Questions When Considering a Machine Learning Deployment Q&A with Forrester Analyst, Mike Gualtieri.

Presented By:

Mike Gualtieri
Mike Gualtieri
VP, Principal Analyst

Mike’s research focuses on artificial intelligence (AI) technologies, platforms, and practices that enable technology professionals to deliver digital transformations that lead to prescient digital experiences and breakthrough operational efficiency. His key technology coverage areas are AI and emerging technologies that make software faster, smarter, and transformative for global enterprises and organizations. He advises enterprise decision makers and executive leaders around the world on the intersection of business strategy, AI, and digital transformation.

Mike is a recipient of the Forrester Courage Award for making bold calls that inspire leaders and guide great business and technology decisions.

He is a frequent and highly sought-after speaker at industry, corporate, educational, and technology events for his audience-designed, insightful, and energetic speeches.

Mike provides technology vendors with actionable, fine-tuned advisory sessions on strategy, messaging, competitive analysis, buyer-persona analysis, market trends, and product roadmaps for the areas he directly covers and adjacent areas that wish to launch into new markets or use new technologies.

John DesJardins
John DesJardins

John DesJardins is currently CTO  at Hazelcast, where he is championing the growth of our Developer and Customer Community. His expertise in large scale computing spans Data Grids, Microservices, Cloud, Big Data, Internet of Things, and Machine Learning. He is an active blogger and speaker. John brings over 20 years of experience in architecting and implementing global scale computing solutions, including working with top Global 2000 companies while at Hazelcast, Cloudera, Software AG and webMethods. He holds a BS in Economics from George Mason University, where he first built predictive models, long before that was considered cool.