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- 2024
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Mark
Predicting dust storm susceptibility: exploring control strategies with XGBoost models
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- Master (Two yrs)
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Mark
Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
(
- Master (Two yrs)
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Mark
Forecasting during recession: Comparing the performance of machine learning and autoregressive models on the Swedish stock market
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- Bach. Degree
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Mark
Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data
2024) In Master Thesis in Geographical Information Science GISM01 20232(
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
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Mark
Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
(
- Bach. Degree
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Mark
Multivariate time series classification in time-sensitive environments using deep learning
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- Master (Two yrs)
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Mark
Prevalent Discord. Exploring and estimating the prevalence of the type of user disagreement on news media Facebook posts discussing the Colombian peace process (2020-2022)
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- Master (Two yrs)
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Mark
Predicting True Sepsis and Culture-positive Sepsis in Intensive Care Unit with Machine Learning Techniques
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- Master (Two yrs)
- 2023
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Mark
Winter Wheat Harvest Prediction Using Primarily Satellite Radar Data from Sentinel-1
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- Master (Two yrs)
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Mark
Maskininlärning & Random Forest: Överträffar traditionella kreditmodeller
(
- Bach. Degree
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Mark
The use of Machine Learning to predict adverse birth outcomes: Empirical real world evidence from a human cohort study in Adama, Ethiopia
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- Master (Two yrs)
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Mark
Modeling German Energy Market Hourly Profiles with a Focus on Variable Renewable Energy
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- Master (One yr)
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Mark
Finding ways of optimizing coagulant dosage, for a more sustainable wastewater treatment process
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- Master (Two yrs)
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Mark
Classifying High-Growth Manufacturing Firms on the Swedish Stock Market:A Comparative Study Between the Logistic Regression, Support Vector Machine and Artificial Neural Network
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- Master (Two yrs)
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Mark
Can Machine Learning improve inflation forecasting?
(
- Master (One yr)