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--- cs501r_f2018:lab3 [2018/09/13 22:46]
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+++ cs501r_f2018:lab3 [2018/09/14 17:49]
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 ====Deliverable:====
-For this lab, you will submit an ipython notebook via learningsuite.
+For this lab, you will submit an ipython notebook via learningsuite.  This is where you build your first deep neural network!
+For this lab, we'll be combining several different concepts that we've covered during class, including new layer types, initialization strategies, and an understanding of convolutions.
 ----
-//Part 0:// Watch and follow video tutorial
+====Grading standards:====
+  * 30% Part 0: Successfully followed lab video and typed in code
+  * 20% Part 1: Re-implement Conv2D and CrossEntropy loss function
+  * 20% Part 2: Implement different initialization strategies
+  * 10% Part 3: Print parameters, plot train/test accuracy
+  * 10% Part 4: Convolution parameters quiz
+  * 10% Tidy and legible figures, including labeled axes where appropriate
+----
+====Detailed specs:====
+**Part 0:** Watch and follow video tutorial
 **Part 1:** Re-implement a Conv2D module  with parameters and a CrossEntropy loss function.
 You will need to use
      https://pytorch.org/docs/stable/nn.html#torch.nn.Parameter

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