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Hakim Elakhrass talks about post-deployment data science, the real-world use cases for tools like NannyML, the potentially catastrophic effects of unmonitored models in production and the most important skills for modern data scientists to cultivate.

Post-Deployment Data Science

https://www.datacamp.com/blog/post-deployment-data-science

Serg Masis talks about the different challenges affecting model interpretability in machine learning, how bias can produce harmful outcomes in machine learning systems and the different types of technical and non-technical solutions to tackling bias. 

Interpretable Machine Learning 

https://www.datacamp.com/blog/interpretable-machine-learning

Sandra Kublik and Shubham Saboo, authors of GPT-3: Building Innovative NLP Products Using Large Language Models shares insights about what makes GPT-3 unique, the transformative use-cases it has ushered in, the technology powering GPT-3, its risks and limits.

GPT-3 and our AI-Powered Future

https://www.datacamp.com/blog/gpt-3-and-our-ai-powered-future

Elettra Damaggio shares how data leaders can balance short-term wins with long-term goals, how to earn trust with stakeholders, major challenges when launching a data science function, and advice she has for new and aspiring data practitioners.

How to Build a Data Science Team from Scratch

https://www.datacamp.com/blog/how-to-build-a-data-science-team-from-scratch

In this episode of DataFramed, we speak with Noah Gift, founder of Pragmatic AI Labs and prolific author about operationalizing machine learning in organizations and his new book Practical MLOPs.

Scaling Machine Learning Adoption: A Pragmatic Approach

https://www.datacamp.com/blog/scaling-machine-learning-adoption-a-pragmatic-approach

In this episode of DataFramed, Adel speaks with Maria Luciana Axente, Responsible AI and AI for Good Lead at PwC UK on the state and future of responsible AI.

The Future of Responsible AI

https://www.datacamp.com/blog/the-future-of-responsible-ai

In this episode of DataFramed, Adel speaks with Alessya Visnjic, CEO and co-founder of WhyLabs, an AI Observability company on a mission to build the interface between AI and human operators.

Operationalizing Machine Learning with MLOps

https://www.datacamp.com/blog/operationalizing-machine-learning-with-mlops

In this episode, Adel speaks with Barr Moses, CEO, and co-founder of Monte Carlo, on the importance of data quality and how data observability creates trust in data throughout

Creating Trust in Data with Data Observability

https://www.datacamp.com/blog/creating-trust-in-data-with-data-observability

Dan Becker deep dives into the intersection of decision sciences and machine learning, how data teams can go from experimentation and deployment to providing value at scale for organizations, and more!

From Predictions to Decisions

https://www.datacamp.com/blog/from-predictions-to-decisions

Sean Law, a Senior Applied Researcher and Data Scientist at TD Ameritrade, talks about data science research and development at TD Ameritrade and much more!

Data Science R&D at TD Ameritrade

https://www.datacamp.com/blog/data-science-randd-at-td-ameritrade

Noemi Derzsy, a Senior Inventive Scientist at AT&amp;T Labs Research within the Data Science and AI Research organization, discusses her work there and much more!

Data Science at AT&T Labs Research

https://www.datacamp.com/blog/data-science-at-atandt-labs-research

Marco Blume, Trading Director at Pinnacle Sports talks about the role of data science in large-scale bets and bookmaking, how Marco is training an army of data scientists and much more.

Data Science, Gambling and Bookmaking

https://www.datacamp.com/blog/marco-and-hugo-discuss-the-role-of-data-science-in-large-scale-bets-and-bookmaking