Data Brew Season 2 Episode 7: Interpretable Machine Learning

Data Brew Season 2 Episode 7: Interpretable Machine Learning

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more. What does it mean for a model to be “interpretable”? Ameet Talwalkar shares his thoughts on IML (Interpretable Machine Learning), how it relates to data privacy and fairness, and his research in this field. See more...

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Episoder(44)

The Power of Synthetic Data | Data Brew | Episode 38

The Power of Synthetic Data | Data Brew | Episode 38

In this episode, Yev Meyer, Chief Scientist at Gretel AI, explores how synthetic data transforms AI and ML by improving data access, quality, privacy, and model training. Highlights include: - Levera...

4 Feb 202542min

Secret to Production AI: Tools & Infrastructure | Data Brew | Episode 37

Secret to Production AI: Tools & Infrastructure | Data Brew | Episode 37

In this episode, Julia Neagu, CEO & co-founder of Quotient AI, explores the challenges of deploying Generative AI and LLMs, focusing on model evaluation, human-in-the-loop systems, and iterative devel...

22 Jan 202537min

Mixture of Memory Experts (MoME) | Data Brew | Episode 36

Mixture of Memory Experts (MoME) | Data Brew | Episode 36

In this episode, Sharon Zhou, Co-Founder and CEO of Lamini AI, shares her expertise in the world of AI, focusing on fine-tuning models for improved performance and reliability. Highlights include: - ...

10 Jan 202541min

Mixed Attention & LLM Context | Data Brew | Episode 35

Mixed Attention & LLM Context | Data Brew | Episode 35

In this episode, Shashank Rajput, Research Scientist at Mosaic and Databricks, explores innovative approaches in large language models (LLMs), with a focus on Retrieval Augmented Generation (RAG) and ...

21 Nov 202439min

Kumo AI & Relational Deep Learning | Data Brew | Episode 34

Kumo AI & Relational Deep Learning | Data Brew | Episode 34

In this episode, Jure Leskovec, Co-founder of Kumo AI and Professor of Computer Science at Stanford University, discusses Relational Deep Learning (RDL) and its role in automating feature engineering....

14 Okt 202443min

LLMs: Internals, Hallucinations, and Applications | Data Brew | Episode 33

LLMs: Internals, Hallucinations, and Applications | Data Brew | Episode 33

Our fifth season dives into large language models (LLMs), from understanding the internals to the risks of using them and everything in between. While we're at it, we'll be enjoying our morning brew. ...

21 Jul 202338min

Demonstrate–Search–Predict Framework | Data Brew | Episode 32

Demonstrate–Search–Predict Framework | Data Brew | Episode 32

We will dive into LLMs for our fifth season, from understanding the internals to the risks of using them and everything in between. While we’re at it, we’ll be enjoying our morning brew. In this sess...

29 Jun 202333min

Generative AI Risks | Data Brew | Episode 31

Generative AI Risks | Data Brew | Episode 31

We will dive into LLMs for our fifth season, from understanding the internals to the risks of using them and everything in between. While we’re at it, we’ll be enjoying our morning brew. In this ses...

8 Jun 202334min

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