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Evaluating models without test data
Practical AI
Optimizing Machine Learning Workflows for Better Model Convergence
This chapter delves into enhancing machine learning workflows, emphasizing strategies for training models that struggle with convergence. Key topics include regularization, hyperparameter tuning, and the use of tools like Weight Watcher for effective model training and automation.
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode