Everything You Need To Know about Probability for Machine Learning

Probability Distributions
Bayes Theory, Naive Bayes, and Optimization
Maximum Likelihood Estimation
Entropy and Cross-Entropy
Log Loss, Brier Skill, and ROC Curves

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Excellent practical guide to many essential metrics in AI & Data Science.

Great read. Crystal clear examples helped to strengthen my understanding of fundamentals like MLE, Bayes applications and Cross entropy.

Jason’s approach of combining theory with hands on implementation is unique and it helped me gain both an intuition and a way to verify the intuition by running simulations. Jason’s method is truly unparalleled. He manages to find the sweet spot between theory and practice. As a practitioner, I was unaware of many theoretical aspects. He contextualized them for me. Thanks for a great job Jason!

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Everything You Need To Know about Probability for Machine Learning

Probability Distributions
Bayes Theory, Naive Bayes, and Optimization
Maximum Likelihood Estimation
Entropy and Cross-Entropy
Log Loss, Brier Skill, and ROC Curves

Check Out What Customers Are Saying:

Excellent practical guide to many essential metrics in AI & Data Science.

Great read. Crystal clear examples helped to strengthen my understanding of fundamentals like MLE, Bayes applications and Cross entropy.

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Probability for Machine Learning

Probability is the bedrock of machine learning. You cannot develop a deep understanding of machine learning without it.

Everything You Need To Know about Probability for Machine Learning

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Everything You Need To Know about Probability for Machine Learning

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