Sökning: "Hyperparameter"

Visar resultat 1 - 5 av 125 uppsatser innehållade ordet Hyperparameter.

  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

  2. 2. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study

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

    Författare :Jonna Matthiesen; [2023-10-24]
    Nyckelord :Compression; Deep Learning; DNN; Hyperparameters; Optimization; Pruning; Hyperparameter Optimisation; Hyperparameter Tuning;

    Sammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER

  3. 3. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskap

    Författare :Stella Jarlöv; Anton Svensson Dahl; [2023]
    Nyckelord :demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

    Sammanfattning : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. LÄS MER

  4. 4. Comparing machine learning algorithms for detecting behavioural anomalies

    Uppsats för yrkesexamina på avancerad nivå, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Fredrik Jansson; [2023]
    Nyckelord :Anomaly Detection; Machine Learning; Behavioural Anomalies;

    Sammanfattning : Background. Attempted intrusions at companies, either from an insider threat orotherwise, is increasing in frequency. Most commonly used is static analysis and filters to stop specific attacks. LÄS MER

  5. 5. Monthly heatwave prediction in Sweden based on Machine Learning techniques with remote sensing data

    Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknik

    Författare :Zhuoran Li; [2023]
    Nyckelord :Heatwave Prediction; Sweden; Machine Learning; Remote Sensing Data; Värmebölja förutsägelse; Sverige; Maskininlärning; Fjärravkänningsdata;

    Sammanfattning : Heatwave events as a kind of extreme climate event, have plagued the human race for the past few years. It severely influences people’s life quality, sometimes even leads to some serious diseases. In order to alleviate the possible damages heatwave events can do, some targeted actions are necessary and forecasting heatwaves is one of them. LÄS MER