TechCrunch
MARCH 31, 2021
We’re living in a phenomenal moment for machine learning (ML), what Sonali Sambhus , head of developer and ML platform at Square, describes as “the democratization of ML.” Snehal Kundalkar is the chief technology officer at Valence. She has been leading Silicon Valley firms for the last two decades, including work at Apple and Reddit.
O'Reilly Media - Data
APRIL 11, 2018
It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.
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O'Reilly Media - Data
APRIL 3, 2018
Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.
Cloudera
JANUARY 9, 2025
Thats why were moving from Cloudera Machine Learning to Cloudera AI. Why AI Matters More Than ML Machine learning (ML) is a crucial piece of the puzzle, but its just one piece. It means combining data engineering, model ops, governance, and collaboration in a single, streamlined environment.
CIO
NOVEMBER 27, 2024
Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.
O'Reilly Media - Data
AUGUST 16, 2018
In this episode of the Data Show , I spoke with Harish Doddi , co-founder and CEO of Datatron , a startup focused on helping companies deploy and manage machine learning models. Today’s data science and data engineering teams work with a variety of machine learning libraries, data ingestion, and data storage technologies.
CIO
SEPTEMBER 29, 2022
And we recognized as a company that we needed to start thinking about how we leverage advancements in technology and tremendous amounts of data across our ecosystem, and tie it with machine learning technology and other things advancing the field of analytics. But we have to bring in the right talent.
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