Multi armed bandits Samenvattingen, Aantekeningen en Examens
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GEORGIA INSTITUTE OF TECHNOLOGY ISYE 6501 FULL COURSE NOTES
- College aantekeningen • 102 pagina's • 2023
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- €16,60
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Week 1 
 
Why Analytics?	6 
Data Vocabulary	7 
Classification	8 
Support Vector Machines	11 
Scaling and Standardization	13 
k-Nearest Neighbor (KNN)	13 
Week 2 
Model Validation	16 
Validation and Test Sets	17 
Splitting the Data	18 
Cross-Validation	20 
Clustering	21 
Supervised vs. Unsupervised Learning	22 
Week 3 
Data Preparation	25 
Introduction to Outliers	25 
Change Detection	27 
Week 4 
Time Series Data	31 
AutoRegressive Integrated Moving Average (ARIMA)	34 
Generalized Autoregressive...
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Georgia Tech Est ISYE 6501 Lecture Transcripts, Comprehensive masterpiece
- Tentamen (uitwerkingen) • 284 pagina's • 2023
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Ook in voordeelbundel
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- €8,06
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Georgia Tech Est ISYE 6501 Lecture Transcripts, Comprehensive masterpiece. 
Document Content and Description Below 
Est ISYE 6501 Lecture Transcripts About This Document This document was originally created in the summer of 2017 and is maintained collaboratively through the efforts of the students of edX GTx ISY E 6501 using transcripts and screenshots from the video lectures. You are strongly encouraged to improve the formatting, layout, add or adjust images, bold key words, and even condense c...
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GEORGIA Tech, ISYE Full course, Graded A+, 2022 update
- Tentamen (uitwerkingen) • 85 pagina's • 2023
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Ook in voordeelbundel
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- €8,06
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GEORGIA Tech, ISYE Full course, Graded A+, 2022 update 
Document Content and Description Below 
Week 1 Why Analytics? 6 Data Vocabulary 7 Classification 8 Support Vector Machines 11 Scaling and Standardization 13 k-Nearest Neighbor (KNN) 13 Week 2 Model Validation 16 Validation and Test Sets 17 Splitting the Data 18 Cross-Validation 20 Clustering 21 Supervised vs. Unsupervised Learning 22 Week 3 Data Preparation 25 Introduction to Outliers 25 Change Detection 27 Week 4 Time Series Data 31 AutoRe...
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ISYE Midterm 2 Notes:Week 8 Variable
- Overig • 16 pagina's • 2022
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- €8,91
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Important to limit the number of factors in the model for 2 reasons: 
o Overfitting – When the number of factors is close to or larger than the number of data 
points the model might fit too closely to random effects 
o Simplicity – on aggregate simple models are better than complex ones. Using less factors 
means that less data is required and the is a smaller chance of including insignificant 
factors. Interpretability is also crucial. Some factors are even illegal to use such as race 
and...
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Lectures - Marketing Analytics for Big Data
- College aantekeningen • 39 pagina's • 2022
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- €6,49
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Duidelijke uitwerking van alle hoorcolleges van het vak Marketing Analytics for Big Data. Inclusief uitgelegde voorbeelden.