edX
MOOC / Non-credit
0
Probability for Machine Learning
About this course
Master probability fundamentals for machine learning. Explore probability rules, distributions, Bayes’ Theorem, and evaluation metrics like ROC and precision-recall curves. Build the skills to interpret uncertainty, model data, and make confident, data-driven decisions in ML applications.
C
67/100
CourseAsk score
- What the provider tells you
- 16/45
- Who stands behind it
- 35/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understand fundamental probability concepts
- apply Bayes' Theorem in practical scenarios
- evaluate models using ROC and precision-recall curves
- interpret uncertainty in data
Machine Learning
#machine learning fundamentals
#data modeling
#probability
#data-driven decisions
#bayes theorem
#uncertainty
#ROC curve
#ml metrics
#precision-recall
$49.00
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- English · 0
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