ML can make your organization more efficient, reduce cost, and increase revenue. If you haven’t developed ML solutions yet, you might want to dig deeper—but what’s the first thing you need to do? Before marching forward with solution discussions, organizations first need to identify the business problem they’re solving for, why, and what their desired outcome is. ML for the sake of ML doesn’t yield valuable results. It’s important to identify the business problems that are a good fit for ML and go from there.
Podcast
Machine Learning for Beginners
If your organization is new to Machine Learning (ML), there are some best practices and common pitfalls about which to be aware. Often, organizations become interested in the promise of ML or they want to play catch-up with their competitors and they decide it’s time to adopt ML too. But it’s not something that happens just because you want it. Often, leaders don’t know what problems ML can solve for or how to make the right business case to reach great results. To be successful, you must first build a strong, core team comprised of the right, cross-functional talent. In this podcast, Vinnie Schoenfelder, Tom Estella, and Ramon Matos dive in on the details of making your new ML initiatives yield powerful results.
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Episode Highlights
Build The Right Team
ML, in many ways, is no different than other successful and unsuccessful projects. In addition to a strong business case, the outcome will be as good as the team you build. Having data scientists on the team is important, but without the right partnership and collaboration, they can only go so far. To start, organizations need to make sure they have a strong, cross-functional team with a high degree of collaboration, including subject matter experts, leadership, and representatives from the areas of the business that will be impacted by the solution.
Tom Estella
Managing Director
Tom is a managing director in CapTech's Atlanta office and leads our firm's machine learning initiatives. He has deep experience scoping, measuring, and creating Advanced Analytical solutions
Vinnie Schoenfelder
CTO
Vinnie is CapTech's Chief Technology Officer and plays a large role in helping define services, forge partnerships, and lead innovation for our clients. As a thought leader, he regularly helps clients solve their most complex business challenges.
Ramon Matos
Director
Ramon is a director in our Atlanta office. He is one of our leading data specialists, working with clients across industries to improve their ability to glean meaningful insights from their data.
