JGS594 Lecture 11

Software Engineering for Machine Learning
Working with a Model
(202202)

Transcript

1. jgs SER 594 Software Engineering for Machine Learning Lecture 11: Working with a Model Dr. Javier Gonzalez-Sanchez javiergs@asu.edu javiergs.engineering.asu.edu | javiergs.com PERALTA 230U Office Hours: By appointment
2. jgs Previously …
3. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 3 jgs Listeners https://refactoring.guru/design-patterns/observer
4. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 4 jgs Listeners // add this before calling fit() model.setListeners(new MyListener());
5. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 5 jgs MyListener
6. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 6 jgs Output …
7. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 7 jgs Output 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381 401 421 441 461 481 501 521 541 561 581 601 621 641 661 681 701 721 741 761 781 801 821 841 861 881 901 921 941 961 981
8. jgs Deploy the Model
9. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 9 jgs Save the Model
10. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 10 jgs Load the Model Load the updater
11. jgs Create an Application Iris Model
12. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 12 jgs Application
13. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 13 jgs Application / / int [] y = model.predict (input) / / y[0]
14. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 14 jgs Can we create a GUI? SEPAL LENGTH: SEPAL WIDTH: PETAL LENGTH: PETAL WIDTH: IRIS TYPE: Calculate
15. jgs Create an Application MNIST Model
16. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 16 jgs Goal
17. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 17 jgs UML
18. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 18 jgs Main.java (1/4)
19. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 19 jgs Main.java (2/4)
20. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 20 jgs Main.java (3/4)
21. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 21 jgs Main.java (4/4)
22. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 22 jgs DrawArea.java (1/2)
23. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 23 jgs DrawArea.java (2/2)
24. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 24 jgs InputImage.java (1/2)
25. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 25 jgs InputImage.java (2/2)
26. jgs Assignment 04 Application
27. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 27 jgs Assignment 04 1. Select a new dataset. Lecture 08 https://archive-beta.ics.uci.edu Your own CSV data from a project you are working on 2. Create a Java Program for training a model until achieving a good performance (0.05). Save the model. This can be console application or GUI. Your choice. 3. Create a Java Application that use the model. It should have a GUI Allow the user to input data: load an image, text, etc. Show a result/classification § You can work in a team of 2 or 3. No more than 3. Individual is OK. § Include Javadoc for classes and methods. https://www.oracle.com/technical-resources/articles/java/javadoc-tool.html § Submit java files. How many files?
28. Javier Gonzalez-Sanchez | SER 594 | Spring 2022 | 28 jgs Questions
29. jgs SER 594 Software Engineering for Machine Learning Javier Gonzalez-Sanchez, Ph.D. javiergs@asu.edu Spring 2022 Copyright. These slides can only be used as study material for the class CSE205 at Arizona State University. They cannot be distributed or used for another purpose.