Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.
Lyft's ML Infrastructure Journey - ML 139
Konstantin Gizdarski is a software engineer at Lyft. They dive deep into the world of machine learning and engineering at Lyft. Join them as they explore the challenges and successes of implementing reinforcement learning, contextual bandits, and advanced AI technologies in a real-world business environment. Learn about the collaborative engineering culture at Lyft, the development of new ML capabilities, and the unique approaches to infrastructure and model deployment. Listen in as industry experts share their insights on accelerating decision-making processes, simplifying tools for end users, and finding innovative solutions to common engineering challenges.
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