Category: Data Science
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The quest for high-quality data
Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. By Ihab Ilyas and Ben Lorica. “AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts,…
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Applications of data science and machine learning in financial services
The O’Reilly Data Show Podcast: Jike Chong on the many exciting opportunities for data professionals in the U.S. and China. In this episode of the Data Show, I spoke with Jike Chong, chief data scientist at…
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Becoming a machine learning company means investing in foundational technologies
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the…
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How AI and machine learning are improving customer experience
From data quality to personalization, to customer acquisition and retention, and beyond, AI and ML will shape the customer experience of the future. By Ben Lorica and Mike Loukides. What can artificial intelligence (AI) and machine learning…
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Real-time entity resolution made accessible
The O’Reilly Data Show Podcast: Jeff Jonas on the evolution of entity resolution technologies. In this episode of the Data Show, I spoke with Jeff Jonas, CEO, founder and chief scientist of Senzing, a startup focused…
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What data scientists and data engineers can do with current generation serverless technologies
The O’Reilly Data Show Podcast: Avner Braverman on what’s missing from serverless today and what users should expect in the near future. In this episode of the Data Show, I spoke with Avner Braverman, co-founder and…
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Specialized tools for machine learning development and model governance are becoming essential
Why companies are turning to specialized machine learning tools like MLflow. By Ben Lorica and Mike Loukides. A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges…
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It’s time for data scientists to collaborate with researchers in other disciplines
The O’Reilly Data Show Podcast: Forough Poursabzi Sangdeh on the interdisciplinary nature of interpretable and interactive machine learning. In this episode of the Data Show, I spoke with Forough Poursabzi-Sangdeh, a postdoctoral researcher at Microsoft Research…
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Algorithms are shaping our lives – here’s how we wrest back control
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Kartik Hosanagar on the growing power and sophistication of algorithms. In this episode of the Data Show, I spoke with Kartik…
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You created a machine learning application. Now make sure it’s secure.
[A version of this post appears on the O’Reilly Radar.] The software industry has demonstrated, all too clearly, what happens when you don’t pay attention to security. By Ben Lorica and Mike Loukides. In a recent…