Sökning: "maskininlärning"

Visar resultat 1 - 5 av 778 uppsatser innehållade ordet maskininlärning.

  1. 1. Classification of a Sensor Signal Attained By Exposure to a Complex Gas Mixture

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Rabnawaz Jan Sher; [2021]
    Nyckelord :Classification; Random Forest; Linear Discriminant Analysis; Naive Bayes; Principal Component Analysis; Drift; Baseline Compensation; Normalization; Sensor; Signal Preprocessing.;

    Sammanfattning : This thesis is carried out in collaboration with a private company, DANSiC AB This study is an extension of a research work started by DANSiC AB in 2019 to classify a source. This study is about classifying a source into two classes with the sensitivity of one source higher than the other as one source has greater importance. LÄS MER

  2. 2. Association between cognitive measures, global brain surface area, genetics, and screen-time in young adolescents : Estimation of causal inference with machine learning

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Evgenija Kravchenko; [2021]
    Nyckelord :Causal modelling; DirectLiNGAM; PGS; intelligence; screen time; cognitive development; Kausal modellering; DirectLiNGAM; PGS; intelligens; skärmtid; kognitiv utveckling;

    Sammanfattning : Screen media activity such as watching TV and videos, playing video games, and using social media has become a popular leisure activity for children and adolescents. The effect of screen time has been a highly debated topic; however, there is still very little known about it. LÄS MER

  3. 3. Application of Deep Q-learning for Vision Control on Atari Environments

    Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik

    Författare :Jim Öhman; [2021]
    Nyckelord :Reinforcement learning; Atari 2600; Deep Q-learning; Myopic Agents; Vision Control; Physics and Astronomy;

    Sammanfattning : The success of Reinforcement Learning (RL) has mostly been in artificial domains, with only some successful real-world applications. One of the reasons being that most real-world domains fail to satisfy a set of assumptions of RL theory. LÄS MER

  4. 4. Machine Learning with Reconfigurable Privacy on Resource-Limited Edge Computing Devices

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

    Författare :Zannatun Nayem Tania; [2021]
    Nyckelord :Data Privacy; Resource Management; Machine Learning; Fitbit; Internet of Things IoT ; Optimization; Dataintegritet; Resurshantering; Machine Learning; Fitbit; Internet of Things IoT ; Optimering;

    Sammanfattning : Distributed computing allows effective data storage, processing and retrieval but it poses security and privacy issues. Sensors are the cornerstone of the IoT-based pipelines, since they constantly capture data until it can be analyzed at the central cloud resources. However, these sensor nodes are often constrained by limited resources. LÄS MER

  5. 5. Encoder-Decoder Networks for Cloud Resource Consumption Forecasting

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

    Författare :Sami Mejdi; [2021]
    Nyckelord :Telecommunications; Cloud; Time Series; Forecasting; Encoder-Decoder; Deep Learning; Machine Learning; Telekommunikation; Moln; Tidsserie; Prognoser; Envoder-Decoder; Djupinlärning; Maskininlärning;

    Sammanfattning : Excessive resource allocation in telecommunications networks can be prevented by forecasting the resource demand when dimensioning the networks and the allocation the necessary resources accordingly, which is an ongoing effort to achieve a more sustainable development. In this work, traffic data from cloud environments that host deployed virtualized network functions (VNFs) of an IP Multimedia Subsystem (IMS) has been collected along with the computational resource consumption of the VNFs. LÄS MER