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Applied Machine Learning: Algorithms

Apr 15, 2024 • Matt Harrison

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About this course

Learn about common machine learning algorithms, their pros and cons, and develop hands-on skills to leverage them.



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Applied machine learning: Algorithms

49s
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What you should know

1m 4s
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K-means

7m 46s
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K evaluation

8m 10s
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Understanding clusters

7m 59s
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Other algorithms

2m 44s
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Challenge: Apply KNN

54s
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Solution: Apply KNN

7m 24s
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PCA

3m 38s
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Structure of components

4m 8s
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Components

5m 23s
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Scatter plot

2m 18s
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Other algorithms

4m
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Challenge: Utilize PCA

34s
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Solution: Utilize PCA

4m 24s
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Linear regression algorithm

4m 34s
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scikit-learn

4m 18s
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Real-world example

6m 14s
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Assumptions

6m 4s
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Challenge: Develop a linear regression model

34s
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Solution: Develop a linear regression model

2m 7s
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Logistic regression algorithm

1m 19s
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Basic example

1m 49s
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Assumptions

4m 7s
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Challenge: Construct a logistic regression model

12s
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Solution: Construct a logistic regression model

4m 50s
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Decision tree algorithm

4m 12s
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Real-world example

6m 28s
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Random Forest and XGBoost

4m 9s
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Challenge: Design a decision tree model

25s
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Solution: Design a decision tree model

4m
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Next steps

1m 26s