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Probability Statistics - The Foundations of Machine Learning - Expected Values - Decision Making Through Probabilities
In this video, we will cover expected values for decision-making through probabilities. This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine Learning".In this...
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Probability Statistics - The Foundations of Machine Learning - Visualizing Joint Distributions - The Road to ML Success
In this video, you will learn how to visualize joint distributions - the road to ML success. This clip is from the chapter "Visualization in Intuition Building" of the series "Probability / Statistics - The Foundations of Machine...
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Probability Statistics - The Foundations of Machine Learning - Exploring Data Types in Code
In this video, you will learn how to explore data types in code. 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...
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Probability Statistics - The Foundations of Machine Learning - Getting Started with Code: Feel of Data
In this video, we will get started with coding. 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 working...
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Probability Statistics - The Foundations of Machine Learning - Distributions - Rationale and Importance
In this video, we will cover distributions for rationale and importance. This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine Learning".In this...
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Probability Statistics - The Foundations of Machine Learning - Quantifying Events - Random Variables
In this video, we will cover quantifying events - random variables. This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine Learning".In this...
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Probability Statistics - The Foundations of Machine Learning - Applying Conditional Probability - Bayes Rule
In this video, you will learn how to apply conditional probability - Bayes rule. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In...
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Probability Statistics - The Foundations of Machine Learning - Simulating Coin Flips for Probability
In this video, we will cover simulating coin flips for probability. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section, we...
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Probability Statistics - The Foundations of Machine Learning - Code Environment Setup and Python Crash Course
In this video, we will first set up the code environment and then have a quick Python crash course. This clip is from the chapter "Diving in with Code" of the series "Probability / Statistics - The Foundations of Machine Learning".In...
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Probability Statistics - The Foundations of Machine Learning - Rules for Counting (Mostly Optional)
In this video, we will cover the rules for counting. 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.
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Probability Statistics - The Foundations of Machine Learning - Introduction to Uncertainty, Probability Intuition
In this video, we will cover a quick introduction to uncertainty, probability intuition. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine...
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Probability Statistics - The Foundations of Machine Learning - Central Tendency, Mean, Median, and Mode
In this video, we will cover central tendency, mean, median, and mode. 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...
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Probability Statistics - The Foundations of Machine Learning - Entropy - The Most Important Application of Expected Values
In this video, we will cover Entropy - the most important application of expected values. This clip is from the chapter "Applications to the Real World" of the series "Probability / Statistics - The Foundations of Machine Learning".In...
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Probability Statistics - The Foundations of Machine Learning - Case Study: Sleep Analysis, Structure, and Code
In this video, we will cover a case study for sleep analysis, structure, and code. This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...
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Probability Statistics - The Foundations of Machine Learning - Two Random Variables - Joint Probabilities
In this video, we will cover two random variables with the help of an example. This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...
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Probability Statistics - The Foundations of Machine Learning - Conditional Probability, the Most Important Concept in Stats
In this video, we will cover conditional probability, the most important concept in stats. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine...
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Fundamentals of Machine Learning - Decision Tree
This video explains a lab session on a decision tree, getting dependencies, and how to create mock data. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab...
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Probability Statistics - The Foundations of Machine Learning - Spam Detection - Implementation Issues
In this video, we will cover spam detection - implementation issues. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section,...
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Probability Statistics - The Foundations of Machine Learning - Continuous Distributions with the Help of an Example
In this video, we will cover continuous distributions - probability densities. This clip is from the chapter "Random Variables - Rationale and Applications" of the series "Probability / Statistics - The Foundations of Machine...
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Practical Data Science using Python - Decision Tree - Learning Steps
This video explains decision tree - learning steps. This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains classification using decision trees.
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Practical Data Science using Python - Decision Tree - Model Optimization using Grid Search Cross Validation
This video explains decision tree - model optimization using grid search cross validation. This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains...
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Practical Data Science using Python - Decision Tree - Gini Index and Entropy Measures
This video explains decision tree - Gini Index and Entropy Measures. This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains classification using...
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Python for Machine Learning - The Complete Beginners Course - What Is Entropy?
In this video, we will understand entropy. This clip is from the chapter "Classification Algorithms: Decision Tree" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover...
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Python for Machine Learning - The Complete Beginners Course - Introduction to Decision Trees
In this video, we will have a quick introduction to decision trees. This clip is from the chapter "Classification Algorithms: Decision Tree" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we...