Machine Learning Foundations Notes
===
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- [Machine Learning Foundations Note](/dCQjfClsTCq1cP0fGrsJrg)
1 - The Learning Problem
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- [The Learning Problem](/DskeVZqsSHed1anXwGA8QQ)
2 - Learning to Answer Yes/No
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- [Learning to Answer Yes/No](/brDN3c3fT_OpQDLilLGkgw)
3 - Types of Learning
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- [Types of Learning](/WwPboGTjQ36EKQgxc4vfDQ)
4 - Feasibility of Learning
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- [Feasibility of Learning](/s5xQisleSESzXTiQMat1ww)
5 - Training versus Testing
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- [Training versus Testing](/8QuBnRv4QveGXnf4dNVOHA)
6 - Theory of Generalization
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- [Theory of Generalization](/9H5RxzfLRUuNRRNuDGw_gw)
7 - The VC Dimension
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- [The VC Dimension](/uRPIqUadQYqJotu5wOJQbg)
8 - Noise and Error
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- [Noise and Error](/OT_lKI7EQO2FSzdrhV43DQ)
9 - Linear Regression
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- [Linear Regression](/BvPjzDsqTkSO9QBuwgaNRQ)
10 - Logistic Regression
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- [Logistic Regression](/Il4xO-CbSj2WSZetLPa7PQ)
11 - Linear Model for Classification
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- [Linear Model for Classification](/guCPHOubSeeeyR333Vqpdw)
12 - Nonlinear Transformation
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- [Nonlinear Transformation](/6Bc4l9JCSp-QvZhZ4tK0-w)
13 - Hazard of Overfitting
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- [Hazard of Overfitting](/bfwWZEY0S0Ou3MJpIbGRGg)
14 - Regularization
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- [Regularization](/tMVl6gFRRJiP9UXka3AfGw)
15 - Validation
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- [Validation](/cEvSOdUoTtaClQd2-ge_gw)
16 - Three Learning Principles
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- [Three Learning Principles](/RYTo8Ws5TPOfrFe9jPxG0g)
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###### tags: `Machine Learning Foundations`
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