Sökning: "Machine Learning Operations"
Visar resultat 1 - 5 av 112 uppsatser innehållade orden Machine Learning Operations.
1. Implementing End-to-End MLOps for Enhanced Steel Production
M1-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)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
2. Risk analysis of implementing Machine Learning in construction projects
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : 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
3. Sales forecasting for supply chain using Artificial Intelligence
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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
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)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
5. A deep learning approach for drilling tool condition monitoring in Raiseboring
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : 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