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Real-Time Insights into ML Model Training with Amazon SageMaker Debugger

Offered By: Toronto Machine Learning Series (TMLS) via YouTube

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Data Science Courses Machine Learning Courses Deep Learning Courses Cloud Computing Courses Amazon Web Services (AWS) Courses Model Optimization Courses Model Training Courses

Course Description

Overview

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Explore the critical role of debugging in machine learning model development through this informative conference talk from the Toronto Machine Learning Series. Discover how Amazon SageMaker Debugger can revolutionize your ML workflow by automatically identifying issues and providing deep insights into models. Learn from AWS experts Nathalie Rauschmayr, Lu Huang, and Satadal Bhattacharjee as they discuss common challenges in ML model training and demonstrate how effective debugging techniques can save time and costs during the prototyping phase. Gain valuable knowledge on leveraging real-time insights to optimize your machine learning projects and enhance overall model performance.

Syllabus

Get Real-Time Insights into ML Model Training with Amazon SageMaker Debugger


Taught by

Toronto Machine Learning Series (TMLS)

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