I'm currently an EE senior who is planning to attend grad school for machine learning. I have a free month of winter break to study a topic of my choice. What would be most helpful for me? I've taken:
- Calc I-III and Diff Eq
- Linear Algebra
- Linear Systems
- Basic Probability and Statistics
- DSP/Image Processing/Other EE classes
- Machine Learning (next semester)
I'm debating studying:
- Optimization (From Nesterov's Introductory Lectures on Convex Optimization)
- Machine Learning (From Bishop's Pattern Recognition and Machine Learning)
- Statistics (Not sure what book)
- Real Analysis (Not sure what book)
If you were in my shoes during your undergrad, what subject do you wish you had studied?
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