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teaching:ft1920:vl:convex [2019/12/09 15:19] ipa [Lecture Notes] |
teaching:ft1920:vl:convex [2019/12/12 14:56] ipa Add logistic loss visualization |
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| We recommend programming the exercises with Python and numpy. | We recommend programming the exercises with Python and numpy. | ||
| A basic understanding of Python and numpy should be sufficient for most exercises. | A basic understanding of Python and numpy should be sufficient for most exercises. | ||
| + | |||
| + | ==== Using Mathematica ==== | ||
| + | Go to the [[https://www.wolfram.com/programming-lab/|Wolfram Programming Lab]] and click on the orange button. | ||
| + | This brings you to a tutorial notebook. With the file menu in the light grey bar you can create an empty notebook. | ||
| + | In the notebook you can paste the code from the code files below. | ||
| + | Execute the code with Shift+Enter. | ||
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| - {{teaching:ft1920:vl:convex:files:uebungsblatt7.pdf | Exercise Sheet 7}} | - {{teaching:ft1920:vl:convex:files:uebungsblatt7.pdf | Exercise Sheet 7}} | ||
| - {{teaching:ft1920:vl:convex:files:uebungsblatt8.pdf | Exercise Sheet 8}} | - {{teaching:ft1920:vl:convex:files:uebungsblatt8.pdf | Exercise Sheet 8}} | ||
| + | - {{teaching:ft1920:vl:convex:files:8_moreauenvelope.pdf | Mathematica code for visualizing the Moreau Envelope}} | ||
| + | - {{teaching:ft1920:vl:convex:files:8_sigmoid.pdf | Mathematica code for visualizing the Sigmoid function}} | ||
| + | - {{teaching:ft1920:vl:convex:files:8_logisticloss.pdf | Mathematica code for visualizing the logistic loss classifier}} | ||
| + | - {{teaching:ft1920:vl:convex:files:uebungsblatt9.pdf | Exercise Sheet 9}} | ||
| + | - {{teaching:ft1920:vl:convex:files:data_exercise_sheet_9.zip | Data}} | ||