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Lecture 12 - Debugging ML Models and Error Analysis | Stanford CS229: Machine Learning (Autumn 2018)

Lecture 12 - Debugging ML Models and Error Analysis | Stanford CS229: Machine Learning (Autumn 2018)

Stanford Online

For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Andrew ...

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25:17

ML Performance Debugging with XProf | JAX/OpenXLA DevLab Fall 2025

ML Performance Debugging with XProf | JAX/OpenXLA DevLab Fall 2025

OpenXLA

Kelvin Le walks through the features of XProf and shows a case study of how different hyperparameters affect performance.

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18:45

How To Debug Deep Learning Programs | A Simple Process Anybody Can Use

How To Debug Deep Learning Programs | A Simple Process Anybody Can Use

Machine Learning with Phil

Dimensional mismatch problems in deep learning programs can be a pain to debug, but I'll show you a simple and repeatable ...

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1:24:02

How to debug machine learning models, from Apple to startup-Gabriel Bayomi-theDataScientistShow#055

How to debug machine learning models, from Apple to startup-Gabriel Bayomi-theDataScientistShow#055

The Data Scientist Show

Gabriel Bayomi is the Co-Founder at OpenLayer, a tool that tests & debugs machine learning models. OpenLayer was in the ...

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41:25

We Need to Talk About ML Debugging by Juliano Tusi Amaral Laganá Pinto

We Need to Talk About ML Debugging by Juliano Tusi Amaral Laganá Pinto

GAIA

We Need to Talk About ML Debugging by Juliano Tusi Amaral Laganá Pinto at the 2026 GAIA Conference. Machine learning ...

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1:37:20

Techniques for ML Model Transparency and Debugging

Techniques for ML Model Transparency and Debugging

Microsoft Research

Without good models and the right tools to interpret them, data scientists risk making decisions based on hidden biases, spurious ...

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5:41

ML Pipeline Debugging: Fixing Invisible Data Drift

ML Pipeline Debugging: Fixing Invisible Data Drift

Master of Machines

Why do flawless machine learning models fail immediately after deployment? It's rarely a flaw in the math; it's the "hidden crisis" of ...

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1:12:43

RL Debugging and Diagnostics | Stanford CS229: Machine Learning Andrew Ng - Lecture 20 (Autumn 2018)

RL Debugging and Diagnostics | Stanford CS229: Machine Learning Andrew Ng - Lecture 20 (Autumn 2018)

Stanford Online

For more information about Stanford's Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Andrew ...

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ML-based Log Analysis for Faster Debugging | Vijaybhasker Pagidoju | Conf42 ML 2025

ML-based Log Analysis for Faster Debugging | Vijaybhasker Pagidoju | Conf42 ML 2025

Conf42

Read the abstract ➤ https://www.conf42.com/Machine_Learning_2025_Vijaybhasker_Pagidoju_debugging_analysis_pattern ...

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Debugging Machine Learning Models | Error Analysis Explained

Debugging Machine Learning Models | Error Analysis Explained

Micro Learning

Building a machine learning model is only half the challenge—**debugging and improving it** is where real AI engineering ...

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47:17

Debugging ML Models? Build a Feature Platform That Actually Works

Debugging ML Models? Build a Feature Platform That Actually Works

InfoQ

Tired of endless debugging cycles in your machine learning models? This video dives deep into how building a robust feature ...

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5:19

Building a Visual Debugging Tool for ML - TF.js in Interactive Visual Analytics (TF Dev Summit '19)

Building a Visual Debugging Tool for ML - TF.js in Interactive Visual Analytics (TF Dev Summit '19)

TensorFlow

Manifold is Uber's model-agnostic visual debugging tool for machine learning. In this talk, we will introduce how we used TF.js to ...

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1:26:55

Dr. Kristian Rother - Best Practices for Debugging

Dr. Kristian Rother - Best Practices for Debugging

PyData

Description This tutorial introduces concepts and techniques for systematic debugging. Participants will debug example programs ...

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59:18

Debugging ML in Production feat. Shreya Shankar | Stanford MLSys Seminar Episode 12

Debugging ML in Production feat. Shreya Shankar | Stanford MLSys Seminar Episode 12

Stanford MLSys Seminars

Episode 12 of the Stanford MLSys Seminar Series! Debugging machine learning in production Speaker: Shreya Shankar Abstract: ...

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20:22

Taming AI Infrastructure Failures with Agentic Debugging | Phillip Liu from Meta

Taming AI Infrastructure Failures with Agentic Debugging | Phillip Liu from Meta

@Scale

NCCL watchdog timeouts are a common failure mode in distributed AI model training. They impact not only Meta, but broadly ...

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36:41

Applied Deep Learning - Troubleshooting and Debugging with Josh Tobin (2019)

Applied Deep Learning - Troubleshooting and Debugging with Josh Tobin (2019)

Weights & Biases

In this Applied Deep Learning Lecture, Josh Tobin presents on debugging and troubleshooting Machine Learning Models, as well ...

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14:53

Lesson4: How to debug a Neural Network part 1

Lesson4: How to debug a Neural Network part 1

AISolutions

In this tutorial we will start to see how to debug a neural network, so this video will be useful for experienced machine learning ...

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13:00

How to Debug PyTorch Source Code - Deep Learning in Python

How to Debug PyTorch Source Code - Deep Learning in Python

deeplizard

In this episode, we learn how to set up debugging for PyTorch source code in Visual Studio Code. VIDEO SECTIONS ...

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9:30

Machine Learning Debugging Explained: Fix AI Models Like a Pro

Machine Learning Debugging Explained: Fix AI Models Like a Pro

Micro Learning

#MachineLearning #ArtificialIntelligence #DeepLearning #MLDebugging #MLOps #DataScience #AIEngineering ...

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What Are Common Debugging Issues In ML Ensemble Pipelines? - AI and Machine Learning Explained

What Are Common Debugging Issues In ML Ensemble Pipelines? - AI and Machine Learning Explained

AI and Machine Learning Explained

What Are Common Debugging Issues In ML Ensemble Pipelines? Are you interested in understanding the common challenges ...


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