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Machine Learning for Biologists

Machine Learning for Biologists
Key Points
Instructor Notes
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Machine Learning for Biologists

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EPISODES

Summary and Schedule

1. Introduction

2. Classifying T-cells

3. Evaluating a Model

4. Decision Trees, Random Forests, and Overfitting

5. Logistic Regression, Artificial Neural Networks, and Linear Separability

6. Understanding Machine Learning Literature

7. Conclusion and next steps

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Acknowledgements
ml4bio Software Introduction
Glossary
Learning goals

References

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