Machine Learning - Final Collaborative Study Guide-comprehensive-2022-2024
Note!!!
• I (who will remain anonymous) really hope everyone can benefit from this study guide!
• Please comment if you feel like some inf
...
Machine Learning - Final Collaborative Study Guide-comprehensive-2022-2024
Note!!!
• I (who will remain anonymous) really hope everyone can benefit from this study guide!
• Please comment if you feel like some information may be wrong but you’re hesitant to change it. (If you’re confident it’s wrong, then change it.)
• PLEASE CONTRIBUTE A LITTLE if you’re gonna use it``
• https://www.cc.gatech.edu/~bboots3/CS4641-Fall2018/Lecture23/Final_Review.pdf
• Final Midterm study guide:
• Feel free to make new outline topics according to the one prof said in class
• Useful Comparison chart for different algorithms: https://www.dataschool.io/comparing- supervised-learning-algorithms/
• excellent youtube videos: search "victor lavrenko" and then a topic ("pca", "svm", etc)
• Happy studying =) <3 <3 <3
Table Of Contents
Similarities / Differences Between Algorithms 1 Supervised Learning 11
Vocab 20
Learning Theory 21 Randomized Optimization 23 Unsupervised learning 25 Clustering 26
Similarities / Differences Between Algorithms
• Decision tree
o Bias: prefer small decision trees
▪ High bias with small decision trees (underfit possible)
▪ low bias with large decision trees but higher variance (because overfit possible)
o Search algorithm: greedy (always makes the choice that seems to be the best at that moment)
o Heuristic function: information gain (choose split with maximum change in entropy)
CONTINUED....
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