Mark Moyou, PhD’s Post

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Sr. Data Scientist @NVIDIA | Host @ AI Portfolio Podcast, Caribbean Tech Pioneers Podcast, Progress Guaranteed Podcast | Director @Optimized AI Conference

Domain expertise has tremendous value in #explainable machine learning. Causality is the bridge to aligning this domain knowledge and understanding why models are guided to a particular response. In episode 12 of the #aiportfolio podcast Serg Masís and I discuss explainable ai and #llms. If you have watched Jon Krohn's show, Super Data Science Podcast, lots of the great technical questions come from Serg Masís, so his insights into #machinelearning in highly regulated environments can expand your knowledge on the topic. One thing that stuck out to me is that if you have an exploration mindset, you can leverage models to help you do better Exploratory Data Analysis vs just visualizing statistics on the data. Links to show are in the comments

Darshil Modi

Creator of AutoMeta RAG framework | Multimodal AI Engineer | Author | Open source contributor | Tech speaker | LLMs, OpenAI, VectorDB, RAG, Huggingface, Computer Vision, Tensorflow, PyTorch, YOLO

4mo

The whole idea of performing EDA is for adding explanability to ML models and helping in ML model selection. How do you feel ML models can help in EDA ? Sounds weird

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Serg Masís

Data Scientist | Interpretable Machine Learning

4mo

Thank you so much for sharing, Mark Moyou, PhD!

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Jon Krohn

Chief Data Scientist 👨🔬 Bestselling Author 📚 SuperDataScience Host 🎙️

4mo

Serg is the man! So great to see him on your podcast, Mark :)

Aayush Bhan

University of Toronto

4mo

Very intuitive. Thanks for sharing. 

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