In this video, you will learn how to apply conditional probability - Bayes rule.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover continuous distributions - probability densities.
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This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover dispersion exploration through code.
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This clip is from the chapter "Measures of Spread" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we will...

In this video, we will cover expected values for decision-making through probabilities.
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This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover distributions for rationale and importance.
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This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover two random variables with the help of an example.
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This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover a case study for sleep analysis, structure, and code.
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This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of...

In this video, you will learn how to visualize joint distributions - the road to ML success.
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This clip is from the chapter "Visualization in Intuition Building" of the series "Probability / Statistics - The Foundations of...

In this video, we will cover the dependence and variance of two random variables.
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This clip is from the chapter "Visualization in Intuition Building" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover Bayesian inference code through PyMC3.
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This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine Learning".In this...

In this video, we will cover central tendency, mean, median, and mode.
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This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we...

Welcome to the course. This is a quick introduction video to the course.
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This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we...

In this video, we will cover conditional probability, the most important concept in stats.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of...

In this video, we will cover a quick introduction to uncertainty, probability intuition.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of...

In this video, we will cover simulating coin flips for probability.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In this...

In this video, we will cover spam detection - implementation issues.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In...

In this video, we will cover the application of the Bayes rule in a real-world example for spam detection.
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This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The...

In this video, you will learn how to explore data types in code.
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This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we will...

In this video, we will cover Entropy - the most important application of expected values.
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This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will cover the rules for counting.<br<br/>/>

This clip is from the chapter "Counting" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, you will learn the rules for counting.

In this video, we will cover quantifying events - random variables.
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This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...

In this video, we will get started with coding.
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This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we will first set up our...

In this video, we will first set up the code environment and then have a quick Python crash course.
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This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine...

In this video, you will learn how to apply Entropy by coding decision trees for machine learning.
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This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of...