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Machine Learning Academy
I attended a program that teaches ML (machine learning). All the machine learning algorithms were made completely from scratch, most without even numpy. There was starter code for separate systems such as the Pac-Man game, but the algorithms themselves were completely made by me. I did not use AI to code the algorithms, although it's possible it was used in some of the starter code. The coolest thing in this program was definitely making an AI that plays Pac-Man.
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Timeline
I had to redo K-means because I had finished it on another computer and didnt get it back. I also added a README.
Finished the last thing: k-nearest-neighbors (knn) classification. Also just had to redo that on my computer. The only thing I haven't done on my yet is cross-validation. I'm not doing that. It's not that its that complicated, it's just boring especially since I've already done it and unnecessary. also didnt do density-based scan for k-means and don't really want to. i got other stuff to do. gonna ship right after i put this on github.
mattseq
13 days ago
Redid the original pacman agent using just a perceptron on my computer. Ran into a few bugs because for some reason they said it was necessary for the classify method to return a list of the best move. This is getting much easier now that I'm doing it all over again multiple times.
Finally did one of the coolest part (in my opinion) of ml: reinforcement learning! We did both Q-learning and Approximate Q-learning. Here's a video of my AI playing Pacman:
we did binary classification and multi-class classification using perceptrons and k nearest neighbor. Right now, I don't have the code for the multi-class classification and knn models because it was done on my partner's computer. We finished early, so the professor gave us some of the real homework she gives her students about k-means clustering (unsupervised learning). So far, I've only done part 1 of that. Also I'm waiting until I have all the starter code at the very least before I make a github repo for all of this.
