Core data preparation features. by Bjørn André Bredesen-Aa (13767126)

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Cross-validation Precision/Recall curves. by Bjørn André Bredesen-Aa (13767126)

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Sequence feature analysis. by Bjørn André Bredesen-Aa (13767126)

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Model outputs and results by Michael Vlah (11441761)

ProSmith model overview. by Alexander Kroll (9304225)

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Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

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Perceptron python code by MOURAD OULID-AISSA (22115083)

“…<p dir="ltr">Perceptron Python code used in project on AI in criminal justice based on a predictive approach to threat detection. …”

SVM python code by MOURAD OULID-AISSA (22115083)

“…<p dir="ltr">SVM python code used in project on AI in criminal justice based on a predictive approach to threat detection. …”

Motif Code Unification and TDCM Supplemental by William Terry (22279591)

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Python code for: Using convolutional neural network to predict remission of diabetes after gastric bypass surgery – a machine learning study from the Scandinavian Obesity Surgery Register by Yang Cao (9509135)

“…<p>The file includes the Python code and annotations of training, validation, and test for the CNN predictive model used in the paper “Using convolutional neural network to predict remission of diabetes after gastric bypass surgery – a machine learning study from the Scandinavian Obesity Surgery Register”.…”

Hyperparameters of the ProSmith gradient boosting models. by Alexander Kroll (9304225)

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Experimental results for solar melting of zinc metal using multi-facet parabolic dish and a cavity receiver by Pieter Bezuidenhout (18333273)

“…</p> <p>Experiments were conducted, each with a unique set of environmental conditions:</p> <ol> <li>Experiment 1 – 26^th of July 2022 = “Exp 1_26072022”</li> <li>Experiment 2 – 04t of August 2022= “Exp 2_04082022”</li> <li>Experiment 3 – 16^th of August 2022= “Exp 3_16082022”</li> <li>Experiment 4 – 21^st of August 2022= “Exp 4_21082022”</li> <li>Experiment 5 – 5^th of September 2022= “Exp 5_05092022”</li> </ol> <p>Also included in the dataset are the original weather data collected on the respective experimental test work days as well as the weather data in the processed form after correcting the weather data to serve as input for the numerical model developed in the Python coding language.</p> <p>Raw weather data:</p> <ol> <li>Exp 1_Weather data_Original_26072022</li> <li>Exp 2_Weather data_Original_04082022</li> <li>Exp 3_Weather data_Original_16082022</li> <li>Exp 4_Weather data_Original_21082022</li> <li>Exp 5_Weather data_Original_05092022</li> </ol> <p>Processed weather data:</p> <ol> <li>Exp 1_Weather data_Post-process_26072022</li> <li>Exp 2_Weather data_Post-process_04082022</li> <li>Exp 3_Weather data_Post-process_16082022</li> <li>Exp 4_Weather data_Post-process_21082022</li> <li>Exp 5_Weather data_Post-process_05092022</li> </ol> <p>In addition to all the weather data and the experimental results collected on the five experimental runs, the dataset also contains the Python code used to predict the zinc temperature in the cavity receiver. …”

The optimal ProSmith models combine predictions based on the multimodal Transformer Network with predictions based on separate numerical representations of proteins and small molec... by Alexander Kroll (9304225)

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Scheme of hippocampal detection and prediction of MTLE with the hippocampus as the epileptogenic area. by Kyoya Sakashita (14670611)

Predictive performance for earthworm species prediction across different classification models and handcrafted features on external validation dataset (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

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Schematic showing how the tracking model uses the inputs to make predictions. by Owen M. O’Connor (11965460)

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Predictive performance for earthworm species prediction across different classification models and deep feature maps on external validation dataset (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

Predictive performance for earthworm species prediction across different classification models and handcrafted features using 10-fold CV (<i>E. fetida</i> vs others). by Saiqa Andleeb (11442771)

Fig 4 - by Xiujie Ge (6831833)