DataHour: Evaluation Criteria for Validating Machine Learning Models
DataHour: Evaluation Criteria for Validating Machine Learning Models
14 Mar 202313:03pm - 14 Mar 202314:03pm
DataHour: Evaluation Criteria for Validating Machine Learning Models
About the Event
Evaluating a machine learning model is a crucial step in the development process as it ensures that the model can generalize well to new data. The evaluation criteria used for a machine learning model depend on the nature of the problem and the type of model used.
In this DataHour, Yagnic will discuss the various evaluation metrics and techniques that are commonly used to assess the performance of machine learning models. He will cover various evaluation metrics such as accuracy, precision, recall, F1 score, ROC-AUC, and more. He will also discuss techniques such as cross-validation and holdout validation that can be used to validate machine learning models.
By the end of this webinar, you will have a better understanding of how to choose the appropriate evaluation criteria and techniques for your machine learning models.
Prerequisites: Enthusiasm of learning new technologies, and good to have a basic knowledge of Data Science and Machine Learning algorithms.
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- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
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