Sökning: "Machine Learning Operations"

Visar resultat 1 - 5 av 112 uppsatser innehållade orden Machine Learning Operations.

  1. 1. Implementing End-to-End MLOps for Enhanced Steel Production

    M1-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

    Författare :Marcus Westin; Jacob Berggren; [2024]
    Nyckelord :MLOps; Azure ML; Machine Learning; Computer Science; Microsoft Azure; MLOps; Azure ML; Maskininlärning; Datavetenskap; Microsoft Azure;

    Sammanfattning : Steel production companies must utilize new technologies and innovations to stay ahead of a highly competitive market. Recently, there has been a focus on Industry 4.0, which involves the digitalization of production to integrate with newer technologies such as cloud solutions and the Internet of Things (IoT). LÄS MER

  3. 2. Risk analysis of implementing Machine Learning in construction projects

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Aki Roy; [2024]
    Nyckelord :Construction; Machine Learning; Unstructured Data; Image Processing; Text Processing; Project Analysis; Data Management; Risk Identification;

    Sammanfattning : Machine Learning has significantly influenced development across domains by leveraging incoming and existing data. However, despite its advancements, criticism persists regarding its failure to adequately address real-world problems, with the construction domain being an example. LÄS MER

  4. 3. Sales forecasting for supply chain using Artificial Intelligence

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Vaibhav Mittal; [2023]
    Nyckelord :AI; sales forecasting; supply chain; predictive analytics; AI; försäljningsprognoser; supply chain; predictiv analys;

    Sammanfattning : Supply chain management and logistics are two sectors currently experiencing a transformation thanks to the advent of AI(Artificial Intelligence) technologies. Leveraging predictive analytics powered by AI presents businesses with novel opportunities to streamline their operations effectively. LÄS MER

  5. 4. Accelerating university-industry collaborations with MLOps : A case study about the cooperation of Aimo and the Linnaeus University

    Master-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Nico Pistor; [2023]
    Nyckelord :MLOps; Machine Learning Operations; Development Process; Machine Learning; Artificial Intelligence; DevOps; Collaboration;

    Sammanfattning : Many developed machine learning models are not used in production applications as several challenges must be solved to develop and deploy ML models. Manual reimplementation and heterogeneous environments increase the effort required to develop an ML model or improve an existing one, considerably slowing down the overall process. LÄS MER

  7. 5. A deep learning approach for drilling tool condition monitoring in Raiseboring

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Hedaya Alyousif; [2023]
    Nyckelord :drilling tool condition; deep learning; drilling signals; CNN; spectrogram; Raisboring;

    Sammanfattning : Drilling tool wear can significantly affect the performance of the drilling operation and add extra cost to it. Accurate detection of drilling tool condition is very important for enabling proactive maintenance, minimizing downtime, and optimizing drilling processes. LÄS MER