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Probability & Statistics for Machine Learning & Data Science

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Understand and apply statistical techniques to quantify prediction uncertainty, analyze probability distributions, and evaluate machine learning model efficacy using interval estimates and margins of error.

Key AI Functions:Probability And Statistics,Machine Learning (ML) Algorithms,Statistical Analysis,Probability,Statistical Hypothesis Testing

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Description for Probability & Statistics for Machine Learning & Data Science

Quantify and describe the inherent uncertainty in the predictions produced by machine learning models.

Visually and intuitively comprehend the characteristics of probability distributions that are frequently employed in the fields of data science and machine learning.

Utilize conventional statistical techniques, including maximum likelihood estimation (MLE) and maximum a priori estimation (MAP), to address machine learning issues.

Evaluate the efficacy of machine learning models by utilizing interval estimates and margin of errors.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by DeepLearning.AI

Duration: 33 hours (approximately)

Schedule: Flexible

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