Essays about: "Standard ML"
Showing result 16 - 20 of 66 essays containing the words Standard ML.
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16. A comparison of different machine learning algorithms applied to hyperspectral data analysis
University essay from Umeå universitet/Institutionen för fysikAbstract : Hyperspectral image analysis works with image data where each pixel contains hundreds of wavelengths acquired from spectral measurements. It is a growing field of research in the sciences and industries because it can distinguish visually similar objects. READ MORE
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17. Antibiotic Susceptibility Testing: Effects Of Variability In Technical Factors On Minimum Inhibitory Concentration Using Broth Microdilution
University essay from Uppsala universitet/Institutionen för medicinsk biokemi och mikrobiologiAbstract : Background Broth microdilution (BMD) is a gold-standard reference method to determine minimum inhibitory concentration (MIC) of antibiotics. For this, a standardized concentration of bacterial inoculum (2e5–8e5 colony-forming units, CFU/ml) is added to progressively higher concentrations of antibiotics. READ MORE
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18. Imbalanced Learning and Feature Extraction in Fraud Detection with Applications
University essay from KTH/Numerisk analys, NAAbstract : This thesis deals with fraud detection in a real-world environment with datasets coming from Svenska Handelsbanken. The goal was to investigate how well machine learning can classify fraudulent transactions and how new additional features affected classification. READ MORE
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19. Accelerating bulk material property prediction using machine learning potentials for molecular dynamics : predicting physical properties of bulk Aluminium and Silicon
University essay from Linköpings universitet/Teoretisk FysikAbstract : In this project machine learning (ML) interatomic potentials are trained and used in molecular dynamics (MD) simulations to predict the physical properties of total energy, mean squared displacement (MSD) and specific heat capacity for systems of bulk Aluminium and Silicon. The interatomic potentials investigated are potentials trained using the ML models kernel ridge regression (KRR) and moment tensor potentials (MTPs). READ MORE
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20. Capacity forecasting for wind farms and connected power transformers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Transformers can be described as ’slumbering giants’ in the electric power system. This marks transformers to be big and expensive parts of equipment. Calling them slumbering refers to the unused capacity in many of them. READ MORE
