Sökning: "supervised-learning"

Visar resultat 1 - 5 av 355 uppsatser innehållade ordet supervised-learning.

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

   Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

   Kandidat-uppsats, Lunds universitet/Fysiska institutionen

   Författare :Max Svensson; [2024]
   Nyckelord :Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

   Sammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER

4. 3. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Markus Jonsson; [2024]
   Nyckelord :Self-supervised learning; Representation learning; Computer vision;

   Sammanfattning : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. LÄS MER

5. 4. Physical Exercise and Fatigue Detection using Machine Learning

   Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Filip Säterberg; Rasmus Nilsson; [2024]
   Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

   Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

7. 5. The influence of data annotation process requirements on performance criteria of ML models

   Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Maab Mohammedali; Muntasir Adam; [2023-08-03]
   Nyckelord :;

   Sammanfattning : The data annotation process is a critical step in the development of machine learning (ML) models, as it entails labeling data to help supervised learning. This study investigates the impact of data annotation process requirements on the performance of ML models. LÄS MER