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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Who is this DataHour for?

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About the Speaker

Yagnic Vanam

Yagnic Vanam

Senior Data Scientist at Impact Analytics

Yagnic is an experienced Artificial Intelligence Engineer with a demonstrated history of working in the computer software industry. He is skilled in Molecular Biology, Biotechnology, Teamwork, Leadership, and Project Management with a strong engineering professional. He holds Master of Technology degree - MTech focused in Biotechnology from Indian Institute of Technology, Kharagpur and is currently working as Senior Data Scientist at Impact Analytics.

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