9/1/17
Watched the Google Developers series "Machine Learning Recipes" episodes 1-5 on YouTube. I did this to collect some introductory information on the aspect of artificial intelligence my thesis project will focus on: Machine Learning. Here's what I learned about:
Episode 1: classifiers, features vs. labels, decision trees
Episode 2: how a decision tree works and how to visualize it
Episode 3: how the best features are simple, independent, and informative
Episode 4: classifiers as functions, review of episodes 1-3
Episode 5: learned a way to code a simple classifier from scratch, learned how the k-NN algorithm works
Then, I watched a YouTube video called "MarI/O: Machine Learning For Video Games," which discussed the evolutionary properties of a particular type of neural network, the training of that neural network, and the concept of a fitness function.
Next thesis class, I plan on watching a ~30 minute introduction to deep learning and neural networks.
Episode 1: classifiers, features vs. labels, decision trees
Episode 2: how a decision tree works and how to visualize it
Episode 3: how the best features are simple, independent, and informative
Episode 4: classifiers as functions, review of episodes 1-3
Episode 5: learned a way to code a simple classifier from scratch, learned how the k-NN algorithm works
Then, I watched a YouTube video called "MarI/O: Machine Learning For Video Games," which discussed the evolutionary properties of a particular type of neural network, the training of that neural network, and the concept of a fitness function.
Next thesis class, I plan on watching a ~30 minute introduction to deep learning and neural networks.
Very cool background. Make sure you are fleshing out your ideas somewhere and that it's reflected here.
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