Episode 52: why do machine learning models fail? [RB]
Episode 47 of the Data Science at Home podcast, hosted by Francesco Gadaleta, titled "Episode 52: why do machine learning models fail? [RB]" was published on January 17, 2019 and runs 15 minutes.
January 17, 2019 ·15m · Data Science at Home
Summary
The success of a machine learning model depends on several factors and events. True generalization to data that the model has never seen before is more a chimera than a reality. But under specific conditions a well trained machine learning model can generalize well and perform with testing accuracy that is similar to the one performed during training. In this episode I explain when and why machine learning models fail from training to testing datasets.
Episode Description
The success of a machine learning model depends on several factors and events. True generalization to data that the model has never seen before is more a chimera than a reality. But under specific conditions a well trained machine learning model can generalize well and perform with testing accuracy that is similar to the one performed during training.
In this episode I explain when and why machine learning models fail from training to testing datasets.
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