https://github.com/stm/emac_2019_sig_quant
https://github.com/stm/emac_2019_sig_quant
Last synced: 11 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/stm/emac_2019_sig_quant
- Owner: stm
- Created: 2019-05-23T16:29:12.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-05-30T07:26:15.000Z (about 7 years ago)
- Last Synced: 2025-07-13T00:42:55.580Z (11 months ago)
- Language: R
- Size: 10 MB
- Stars: 5
- Watchers: 4
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## EMAC SIG Quantitative Marketing: Quantitative Marketing Research - Hot Topics and Recent Developments
Github page for the [2019 EMAC Conference](https://www.emac-2019.org) SIG Quantitative Marketing.\
Session Chair: [Dominik Papies](http://uni-tuebingen.de/en/143107)
### Managing and Analyzing Big Data
Speaker: [Klaus Miller](https://sites.google.com/view/klausmiller)
* Slides: [big_data_klaus_miller.pdf](big_data/big_data_klaus_miller.pdf)
* R-Code: [sparklyr demo](https://stm.github.io/emac_2019_sig_quant/big_data.html)
### What is deep learning, and why should I care?
Speaker: [Stefan Mayer](https://uni-tuebingen.de/en/148617)
* Slides: [deep_learning_stefan_mayer.pdf](deep_learning/deep_learning_stefan_mayer.pdf)
* R-Codes
* data preprocessing: [R file](deep_learning/flickr27_data_preprocessing.R)
* training a model from scratch: [documentation](https://stm.github.io/emac_2019_sig_quant/deep_learning_from_scratch.html) / [R file](deep_learning/brand_logos_binary_from_scratch.R)
* transfer learning: [documentation](https://stm.github.io/emac_2019_sig_quant/transfer_learning.html) / [R file](deep_learning/brand_logos_binary_transfer_learning.R)
* transfer learning (multiclass prediction): [documentation](https://stm.github.io/emac_2019_sig_quant/transfer_learning_multi.html) / [R file](deep_learning/brand_logos_categorical_transfer_learning.R)
### Sign and order constraints in hierarchical prior distributions and its benefits for counterfactual predictions
Speaker: [Max Pachali](https://sites.google.com/site/mjpachali/)
* Slides: [value_constraints_pachali.pdf](sign_order_constraints/Sign_Order_Constraints_Value_EMAC_SIG_19.pdf)
* R-Code: [Main R file](sign_order_constraints/Higher_MQSandCW_Benefits_Constraints_Main.R)