Essays about: "Hannes Kindbom"

Found 3 essays containing the words Hannes Kindbom.

1. 1. Investigating the Attribution Quality of LSTM with Attention and SHAP : Going Beyond Predictive Performance

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Hannes Kindbom; [2021]
   Keywords : Digital marketing; Attribution modelling; Multi-touch attribution; Deep learning; LSTM; SHAP; Attention; Interpretability; Digital marknadsföring; Attributionsmodellering; Multi-touch attribution; Djupinlärning; LSTM; SHAP; Attention; Tolkningsbarhet;

   Abstract : Estimating each marketing channel’s impact on conversion can help advertisers develop strategies and spend their marketing budgets optimally. This problem is often referred to as attribution modelling, and it is gaining increasing attention in both the industry and academia as access to online tracking data improves. READ MORE

3. 2. Insights on Creating a Growth Machine Using Attribution Modelling

   University essay from KTH/Optimeringslära och systemteori

   Author : Hannes Kindbom; Viktor Reineck; [2021]
   Keywords : Digital marketing; Attribution modelling; Last-touch attribution; Multi-touch attribution; Simple probabilistic; Logistic regression; Digital marknadsföring; Attributionsmodellering; Last-touch attribution; Multi-touch attribution; Simpel probabilistisk; Logistisk regression;

   Abstract : Given access to detailed tracking data, the problem of attribution modelling has recently gained attention in both academia and the industry. Being able to determine the influence of each marketing channel in driving conversions can help advertisers to allocate their marketing budgets accordingly and ultimately increase their customer base and achieve a higher Return On Investment (ROI). READ MORE

4. 3. LSTM vs Random Forest for Binary Classification of Insurance Related Text

   University essay from KTH/Matematisk statistik

   Author : Hannes Kindbom; [2019]
   Keywords : Random Forest; Classification; Natural Language Processing; Machine Learning; Neural Networks; Bag of Words; Bachelor Thesis; Diffusion of Innovation; Adoption Rate; User Experience; Random Forest; Klassificering; Språkteknologi; Maskininlärning; Neurala nätverk; Bag of Words; Kandidatexamensarbete; Användarupplevelse;

   Abstract : The field of natural language processing has received increased attention lately, but less focus is put on comparing models, which differ in complexity. This thesis compares Random Forest to LSTM, for the task of classifying a message as question or non-question. READ MORE