A Guide to Differential Privacy at Scale
Introduction The growth of AI and machine learning (ML) has led researchers to think, research and stress the development of ethical AI solutions - with AI models / solutions able to provide:
Data Science Opportunities and Challenges in Retail amidst COVID-19
COVID-19 has turned the retail and e-commerce ecosystem upside down. While some businesses have seen a drastic decrease in sales, others have experienced a boom and marched to the forefront of the very competitive industry.
Using machine learning for content recommendations: Q&A with The New York Time's data science director
During our recent Data Science Salon Virtual conference for the media, advertising and entertainment industries, we had Anne Bauer with us from The New York Times. She gave one of our most viewed talks about how The New York Times experiments with personalized recommendations. We received great.
Top 25 Data Science Influencers to Follow in 2022
Top 25 Data Science Influencers to Follow in 2022 In the current times of COVID-19, we rely on exchanging information online, now more than ever. Keeping track of the latest open source library, a new algorithm or recently published paper can be hard or impossible on a daily basis. Fortunately,.
The Data Diet: How Data Journalism Becomes Sustainable
My pandemic media diet has been mostly newsletters and podcasts. I start my day with The New York Times and Morning Brew, and I end it questioning whether the CIA wrote one of the great post-Cold War rock ballads while cooking dinner.
#BlackoutTuesday
Data Science Salon posted a message on Monday expressing our support for our community and our commitment to equality, respect, and human rights. We are participating in #BlackoutTuesday by not posting at all. For the remainder of the week, our social media content will be focused on sharing.
Full Exposure: What Would Life Be Like Without Privacy?
Artificial intelligence in media, entertainment, and advertising promises euphoric convenience: perfect satisfaction for consumers who reveal their personal information. There’s a connection between that exchange and a famous philosophical thought experiment from the 1970s.
Bias and Interpretability in Machine Learning
Presented by Fatih Akici – Manager, Risk Analytics and Data Science at Populus Financial Group during Data Science Salon Austin, you can watch the full talk here. As intelligent systems deepen their footprints in our daily lives, algorithmic bias becomes a more prominent problem in today’s world..
Leveraging Machine Learning and Open Data for Smart Cities
Based on a presentation by Priscilla Boyd – Senior Manager, Data Analytics at Siemens Mobility, watch the full presentation here.
What Indeed’s Job Market Data Tells Us About Trends in Data Science
Based on a presentation by Chris Lindner – Manager, Product Science at Indeed, watch the full presentation here.
