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forecasting:meeting_minutes_september_27_2016 [2016/09/28 03:28] jobatake [Machine Learning] |
forecasting:meeting_minutes_september_27_2016 [2021/09/19 21:59] (current) |
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====== Forecasting Meeting Minutes for Week of September 27, 2016 ====== | ====== Forecasting Meeting Minutes for Week of September 27, 2016 ====== | ||
- | ** Present: Gordon, Brieanna, Jaimie ** | + | ** Present Tuesday: Gordon, Brieanna, Jaimie ** |
+ | |||
+ | ** Present Thursday: Gordon, Brieanna, Jaimie, Austin ** | ||
===== Updates ===== | ===== Updates ===== | ||
* More coordination with Seyyed | * More coordination with Seyyed | ||
+ | |||
+ | ===== Meeting with Dr. Kuh ===== | ||
===== Expectations ===== | ===== Expectations ===== | ||
* 1. Well documented code | * 1. Well documented code | ||
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===== Machine Learning ===== | ===== Machine Learning ===== | ||
Know linear, unsupervised and classification | Know linear, unsupervised and classification | ||
- | * 2 types of algorithms: | + | * 2 types of algorithms: |
* Regression/Estimation | * Regression/Estimation | ||
* Classification (binary/descrete)/Detection | * Classification (binary/descrete)/Detection | ||
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* Multi-learning networks: | * Multi-learning networks: | ||
* Deep learning | * Deep learning | ||
- | * Andrew Ing coursera | + | * Andrew Ng coursera |
+ | |||
+ | ===== Group Progress ===== | ||
+ | * Worked on implementation of Recursive Algorithm | ||
+ | * Compared computation time with Regression | ||
+ | * Derived relationship between samples and computation time for algorithms | ||
===== Reminders ===== | ===== Reminders ===== | ||