Days 18-21

I was out of town for these few days. I hope I didn't miss too much.

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Day 8

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Today Joe came back for morning meetings and Nate left to run in the mountains. Ron's supposed to be back tomorrow. Over the weekend, I collected data for the CAE experiments, so I don't have any more work with that until Ron gets back. So, I started looking at the ladder network architecture Ron implemented with TensorFlow. It's probably the most intricate model I've looked at thus far, but like anything else, it slowly made sense as I broke it down. The papers I read earlier helped a lot by providing a general deconstruction of the model. I used these papers, example code, and a healthy dose of common sense to document the code. I had a lot of downtime, so I did some reading and personal experimentation. In particular, I wanted to get familiar with what HSI data looks and feels like. Here's the result of a small script I wrote: This is a visualization of the 103 bands included in the Pavia University HSI dataset. On the right, brighter colors show higher refl...
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Day 15

Today I made a lot of slow and steady progress. With the paper and the CAE experiment out of the way (for now), I focused on the ladder network code. First, I adapted the code to be object-oriented, so that it would (mostly) work within our pipeline. Every few iterations, I tested the code with Pavia U and MNIST, just to make sure I didn't stray away from the 80% and 98% I achieved earlier. I would guess that failing to do so is what gives rise to hard-to-trace bugs, and nobody likes those. There was one issue where the model would crash and burn around epoch 50, and predict nothing at all. This might be linked to the NaN loss that was occurring in the previous ladder network code, and I think I've found the solution. Whether I have succeeded or failed will be in tomorrow's blog post. I haven't had enough time to run >50 epochs with the fix yet, and everybody likes a good cliffhanger. Tune in next week to find out who shot Nate and the real reason he left to run in t...
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Day 7

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This morning, Ron sent me some instructions on building a neural network in keras, saving me from having nothing to do for the entire day. Nice! I kept the experiment running in the background while I worked on the neural network. Fortunately (or unfortunately) keras made it very easy to create a sophisticated and successful model. I finished testing everything I needed to by midday. Nice? After lunch, there was still stuff to do. As per usual, I did some reading. I highly recommend the notes from Andrej Karpathy's class on using CNNs for visual recognition ( link ). In my Day 2 blog post , I mentioned trying to help Nate format his data to be compatible with the SVM. We are seven days into the internship, and nothing has changed. I figured out how to format my data for the image classification pipeline (one of our internship projects) two days ago, and this format happens to be different. Explaining this format and my implementation to Nate was pretty difficult, and I had a naggi...
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