The Data Exchange Podcast: Nicolas Hohn on challenges and best practices for using RL and machine learning in the enterprise.
Tag: ray
The Future of Machine Learning Lies in Better Abstractions
The Data Exchange Podcast: Travis Addair on how higher levels of abstractions enable non-experts to build efficient machine learning models.
How Technology Companies Are Using Ray
The Data Exchange Podcast: Zhe Zhang describes how companies are using Ray in large-scale production applications.
Connecting Reinforcement Learning to Simulation Software
The Data Exchange Podcast: Max Pumperla on why he’s bullish on Tune, training data scientists, and contributing to open source.
Tools for scaling machine learning
The Data Exchange Podcast: Paco Nathan, Jenn Webb, and Ben Lorica on Ray as a framework for building frameworks, and … More
Building open source developer tools for language applications
The Data Exchange Podcast: Matthew Honnibal on spaCy, Thinc, Prodigy and natural language technologies.
Improving performance and scalability of data science libraries
The Data Exchange Podcast: Wes McKinney on the importance of having a shared infrastructure for data science.
Hyperscaling natural language processing
The Data Exchange Podcast: Edmon Begoli on distributed online learning and its applications in public health.
Scalable Machine Learning, Scalable Python, For Everyone
The Data Exchange Podcast: Dean Wampler on Ray, distributed systems, and Scala and Python.