The Data Exchange with Ben Lorica
Podcast tekijän mukaan Ben Lorica - Torstaisin
281 Jaksot
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Why You Need a Modern Metadata Platform
Julkaistiin: 11.11.2021 -
Making Large Language Models Smarter
Julkaistiin: 4.11.2021 -
AI Begins With Data Quality
Julkaistiin: 28.10.2021 -
Modernizing Data Integration
Julkaistiin: 21.10.2021 -
Deploying Machine Learning Models Safely and Systematically
Julkaistiin: 14.10.2021 -
Large-scale machine learning and AI on multi-modal data
Julkaistiin: 7.10.2021 -
Machine Learning in Astronomy and Physics
Julkaistiin: 30.9.2021 -
The Unreasonable Effectiveness of Multiple Dispatch
Julkaistiin: 23.9.2021 -
How To Lead In Data Science
Julkaistiin: 16.9.2021 -
Why interest in graph databases and graph analytics are growing
Julkaistiin: 9.9.2021 -
The State of Data Journalism
Julkaistiin: 2.9.2021 -
Auditing machine learning models for discrimination, bias, and other risks
Julkaistiin: 26.8.2021 -
An oscilloscope for deep learning
Julkaistiin: 19.8.2021 -
What’s new in data engineering
Julkaistiin: 12.8.2021 -
The evolution of the data science role and of data science tools
Julkaistiin: 5.8.2021 -
Data Augmentation in Natural Language Processing
Julkaistiin: 29.7.2021 -
Storage Technologies for a Multi-cloud World
Julkaistiin: 22.7.2021 -
Building a next-generation dataflow orchestration and automation system
Julkaistiin: 15.7.2021 -
Building a flexible, intuitive, and fast forecasting library
Julkaistiin: 8.7.2021 -
Neural Models for Tabular Data
Julkaistiin: 1.7.2021
A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].
