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/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/24. Logistic Regression Algorithm.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/22. Logistic Regression.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/10. Perceptron Algorithm.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/04. Linear Boundaries.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/13. Log-loss Error Function.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/14. Discrete vs Continuous.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/05. Higher Dimensions.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/09. Perceptron Trick.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/11. Non-Linear Regions.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/26. Notebook Gradient Descent.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/29. Non-linear Data.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/44. Random Restart.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/45. Vanishing Gradient.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/20. Cross-Entropy 2.html

/Part 01-Module 01-Lesson 02_Introduction to Neural Networks/21. Multi-Class Cross Entropy.html

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