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| ====Deliverable:==== | ====Deliverable:==== | ||
| - | For this lab, you will submit an ipython notebook via colab. This notebook will have two parts: | + | For this lab, you will submit an ipython notebook via learningsuite. This notebook will have two parts: |
| **Part 1:** Your notebook should generate a random image. We will run this | **Part 1:** Your notebook should generate a random image. We will run this | ||
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| [[https://colab.research.google.com/drive/1TzaPS3jvRadN-URLbQ9nD1ZNoZktfNRy|A colab notebook teaching you how to use colab notebooks]] | [[https://colab.research.google.com/drive/1TzaPS3jvRadN-URLbQ9nD1ZNoZktfNRy|A colab notebook teaching you how to use colab notebooks]] | ||
| + | |||
| + | [[https://sites.google.com/site/artml2018/tutorials|Various colab tutorials]] | ||
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| type, such as random lines, and can be created in a loop). We won't | type, such as random lines, and can be created in a loop). We won't | ||
| count the number of elements; this is just to encourage you to create | count the number of elements; this is just to encourage you to create | ||
| - | random images with moderate complexity. | + | random images with moderate complexity (ie, you can't just generate randomly colored pixels, as in the example below). |
| For part 2, you should visit the Tensorflow playground (see link above), and play with different settings. Most of it will be unfamiliar, but don't worry -- you can't break it! | For part 2, you should visit the Tensorflow playground (see link above), and play with different settings. Most of it will be unfamiliar, but don't worry -- you can't break it! | ||
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| - | ====Installing anaconda:==== | + | ====Starter code:==== |
| Here's some starter code to help you generate an image. The ''nbimage'' function will display the image inline in the notebook: | Here's some starter code to help you generate an image. The ''nbimage'' function will display the image inline in the notebook: | ||