Essays about: "pre understanding"
Showing result 1 - 5 of 555 essays containing the words pre understanding.
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1. Analyzing the Effects of Virtualization on Cloud Platform Performance
University essay from Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)Abstract : Denna avhandling utforskar den komplexa interaktionen mellan virtualiseringstekniker och prestanda för molnapplikationer. Genom att utvärdera hypervisor- och containerbaserade metoder skapar vi en teoretisk grund för att förstå rollen för virtualisering i modern molnbaserad miljö. READ MORE
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2. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. READ MORE
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3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
University essay from Lunds universitet/Fysiska institutionenAbstract : 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. READ MORE
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4. Implementing End-to-End MLOps for Enhanced Steel Production
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : 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). READ MORE
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5. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE