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Discover principles for great ML product design, data collection and packaging outputs into slick user design. 

Building Great Machine Learning Products at Opendoor

Derek Cedillo is a Senior Manager with over 25 years working in data at GE Aerospace, in the episode he shares the key components to successfully managing data science program within a large and highly regulated organization. 

How the Aviation Industry Leverages Data Science

Jean-Francois Puget is a Distinguished Engineer at NVIDIA and a 3x Kaggle Grandmaster. We talk competitive machine learning and computing on GPUs.

Becoming a Kaggle Grandmaster

George Trujillo shares how he believes real-time data can completely transform the way companies work with data, the real-world use cases of real-time analytics, why reducing data complexity is key to improving the customer experience, the common probl

How Real Time Data Accelerates Business Outcomes

https://www.datacamp.com/blog/how-real-time-data-accelerates-business-outcomes

Daniel Situnayake talks about his work with EdgeML, the biggest challenges in embedded machine learning, potential use cases of machine learning models in edge devices, and the best tips for aspiring machine learning engineers and data science practiti

Embedded Machine Learning on Edge Devices

https://www.datacamp.com/blog/embedded-machine-learning-on-edge-devices

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, the most important skills for modern data scientists to cultivate, and

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, the different types of technical and non-technical solutions to tackling bias, the

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

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.&nbsp;</

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.&nbsp;

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.&nbsp;

Operationalizing Machine Learning with MLOps

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