Udacity AI Programming with Python Nanodegree nd089 v1

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/35. Pre-Lab Analyzing Student Data.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/36. Notebook Analyzing Student Data.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/26. Pre-Lab Gradient Descent.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/30. Non-linear Data.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/17. One-Hot Encoding.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/31. Non-Linear Models.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/27. Notebook Gradient Descent.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/28. Perceptron vs Gradient Descent.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/05. Linear Boundaries.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/32. Neural Network Architecture.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/13. Error Functions.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/12. Non-Linear Regions.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/08. Why Neural Networks.html

/Part 05-Module 01-Lesson 01_Introduction to Neural Networks/19. Maximizing Probabilities.html

Showing first 15 files of 2303 total files