Building a Recommendation System with Hugging Face Transformers
KDnuggets
AUGUST 20, 2024
Learn how to build the recommendation system with advanced technology.
KDnuggets
AUGUST 20, 2024
Learn how to build the recommendation system with advanced technology.
Data Engineering Podcast
MAY 18, 2024
Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Are data agents harder to build?
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Data Engineering Podcast
MAY 26, 2024
Summary Any software system that survives long enough will require some form of migration or evolution. When that system is responsible for the data layer the process becomes more challenging. As you have gone through successive migration projects, how has that influenced the ways that you think about architecting data systems?
Cloudera
NOVEMBER 1, 2024
It also provided a moment for us to launch an important initiative for Cloudera: our Women Leaders in Technology (WLIT) initiative. Building Inclusive Data-Driven Organizations: Leadership Strategies for the Modern Workplace As it stands, women currently account for approximately 25% of the technology workforce.
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Data Engineering Podcast
FEBRUARY 25, 2024
Summary Building a database engine requires a substantial amount of engineering effort and time investment. Over the decades of research and development into building these software systems there are a number of common components that are shared across implementations. Your first 30 days are free!
Data Engineering Podcast
DECEMBER 3, 2023
Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.
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