Essays about: "implementation machine design"

Showing result 1 - 5 of 165 essays containing the words implementation machine design.

1. 1. ML implementation for analyzing and estimating product prices

   University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Author : Abel Getachew Kenea; Gabriel Fagerslett; [2024]
   Keywords : Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

   Abstract : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. READ MORE

3. 2. Machine learning for molecular property prediction and drug safety

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Kinga Jenei; [2023-10-23]
   Keywords : Molecular property prediction; Acid dissociation constant; pKa; Machine learning; Graph Neural Networks; Molecular descriptors; Drug Discovery;

   Abstract : Utilizing machine learning methods for the prediction of acid dissociation (pKa ) values of compounds holds great significance, as pKa is an important parameter, optimized frequently in drug discovery. Accurate prediction of pKa values could potentially provide valuable insights on other molecular properties and thereby support compound design. READ MORE

4. 3. A Software Process Workflow for Smart Anomaly Detection Systems

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Vernita Gouws; [2023-08-16]
   Keywords : anomaly detection; predictive maintenance; machine learning; workflow; software engineering process; lifecycle;

   Abstract : The use of smart anomaly detection systems is set to increase at organisations during the Industry 4.0 era, for use in Predictive Maintenance (PdM). READ MORE

5. 4. State Machine Model-To-Code Transformation In C

   University essay from Uppsala universitet/Signaler och system

   Author : Jonathan Carlgren; Per William Oskarsson; [2023]
   Keywords : State Machine; Model To Code; C; UML; ElementTree; XMI; Programming; Python; Benchmark;

   Abstract : A state machine model can turn a complex behavioural system into a more accessible graphical model, and can improve the way people work with system design by making it easier to communicate and understand the system. The clear structure of a state machine model enables automatic generation of well structured, and consequently readable, and maintainable code. READ MORE

6. 5. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

   University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Author : Ilya Ploshchik; [2023]
   Keywords : Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

   Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE