{"id":21358347,"url":"https://github.com/stm/emac_2019_sig_quant","last_synced_at":"2025-07-23T02:04:28.048Z","repository":{"id":87982630,"uuid":"188270336","full_name":"stm/emac_2019_sig_quant","owner":"stm","description":null,"archived":false,"fork":false,"pushed_at":"2019-05-30T07:26:15.000Z","size":10532,"stargazers_count":5,"open_issues_count":0,"forks_count":6,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-07-13T00:42:55.580Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/stm.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-05-23T16:29:12.000Z","updated_at":"2019-06-02T09:31:13.000Z","dependencies_parsed_at":"2023-05-22T06:15:33.937Z","dependency_job_id":null,"html_url":"https://github.com/stm/emac_2019_sig_quant","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/stm/emac_2019_sig_quant","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stm%2Femac_2019_sig_quant","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stm%2Femac_2019_sig_quant/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stm%2Femac_2019_sig_quant/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stm%2Femac_2019_sig_quant/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stm","download_url":"https://codeload.github.com/stm/emac_2019_sig_quant/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stm%2Femac_2019_sig_quant/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266604009,"owners_count":23954725,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-23T02:00:09.312Z","response_time":66,"last_error":null,"robots_txt_status":null,"robots_txt_updated_at":null,"robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-22T05:15:46.733Z","updated_at":"2025-07-23T02:04:28.043Z","avatar_url":"https://github.com/stm.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"## EMAC SIG Quantitative Marketing: Quantitative Marketing Research - Hot Topics and Recent Developments\n\nGithub page for the [2019 EMAC Conference](https://www.emac-2019.org) SIG Quantitative Marketing.\\\nSession Chair: [Dominik Papies](http://uni-tuebingen.de/en/143107)\n\n### Managing and Analyzing Big Data\n\nSpeaker: [Klaus Miller](https://sites.google.com/view/klausmiller)\n\n* Slides: [big_data_klaus_miller.pdf](big_data/big_data_klaus_miller.pdf)\n* R-Code: [sparklyr demo](https://stm.github.io/emac_2019_sig_quant/big_data.html)\n\n### What is deep learning, and why should I care?\n\nSpeaker: [Stefan Mayer](https://uni-tuebingen.de/en/148617)\n\n* Slides: [deep_learning_stefan_mayer.pdf](deep_learning/deep_learning_stefan_mayer.pdf)\n* R-Codes\n  * data preprocessing: [R file](deep_learning/flickr27_data_preprocessing.R)\n  * 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)\n  * transfer learning: [documentation](https://stm.github.io/emac_2019_sig_quant/transfer_learning.html) / [R file](deep_learning/brand_logos_binary_transfer_learning.R)\n  * 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)\n\n\n### Sign and order constraints in hierarchical prior distributions and its benefits for counterfactual predictions\n\nSpeaker: [Max Pachali](https://sites.google.com/site/mjpachali/)\n\n* Slides: [value_constraints_pachali.pdf](sign_order_constraints/Sign_Order_Constraints_Value_EMAC_SIG_19.pdf)\n* R-Code: [Main R file](sign_order_constraints/Higher_MQSandCW_Benefits_Constraints_Main.R)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstm%2Femac_2019_sig_quant","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstm%2Femac_2019_sig_quant","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstm%2Femac_2019_sig_quant/lists"}