Sökning: "Inlärningsmodeller"

Visar resultat 1 - 5 av 13 uppsatser innehållade ordet Inlärningsmodeller.

  1. 1. Decentralized Large-Scale Natural Language Processing Using Gossip Learning

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

    Författare :Abdul Aziz Alkathiri; [2020]
    Nyckelord :gossip learning; decentralized machine learning; distributed machine learning; NLP; Word2Vec; data privacy; skvallerinlärning; decentraliserad maskininlärning; distribuerad maskininlärning; naturlig språkbehandling; Word2Vec; dataintegritet;

    Sammanfattning : The field of Natural Language Processing in machine learning has seen rising popularity and use in recent years. The nature of Natural Language Processing, which deals with natural human language and computers, has led to the research and development of many algorithms that produce word embeddings. LÄS MER

  2. 2. A Deep Learning Approach to Predicting the Length of Stay of Newborns in the Neonatal Intensive Care Unit

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

    Författare :Bas Theodoor Straathof; [2020]
    Nyckelord :Deep Neural Networks; Electronic Health Records; Length-of-Stay Prediction; Multivariate Time Series Classification; Djupa Neurala Nätverk; Elektroniska Hälsoregister; Klassificering av Multivariat Tidsserie; Förutsägelse av Vistelsetid;

    Sammanfattning : Recent advancements in machine learning and the widespread adoption of electronic healthrecords have enabled breakthroughs for several predictive modelling tasks in health care. One such task that has seen considerable improvements brought by deep neural networks is length of stay (LOS) prediction, in which research has mainly focused on adult patients in the intensive care unit. LÄS MER

  3. 3. Predicting House Prices on the Countryside using Boosted Decision Trees

    Master-uppsats, KTH/Matematisk statistik

    Författare :War Revend; [2020]
    Nyckelord :Machine Learning; Predicting House Prices; Shrinkage Methods; Random Forest; Decision Tree; AdaBoost; Gradient Boosting; LightGBM; CatBoost; XGBoost; Maskininlärning; Förutseende av Huspriser; Krympningsmetoder; Random Forest; Beslutsträd; AdaBoost; Gradient Boosting; LightGBM; CatBoost; XGBoost;

    Sammanfattning : This thesis intends to evaluate the feasibility of supervised learning models for predicting house prices on the countryside of South Sweden. It is essential for mortgage lenders to have accurate housing valuation algorithms and the current model offered by Booli is not accurate enough when evaluating residence prices on the countryside. LÄS MER

  4. 4. Swedish NLP Solutions for Email Classification

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

    Författare :John Robert Castronuovo; [2020]
    Nyckelord :;

    Sammanfattning : Assigning categories to text communications is a common task of Natural Language Processing (NLP). In 2018, a new deep learning language repre- sentation model, Bidirectional Encoder Representations from Transformers (BERT), was developed which can make inferences from text without task specific architecture. LÄS MER

  5. 5. Prediction of Optimal Packaging Solution using Supervised Learning Methods

    Master-uppsats, KTH/Matematisk statistik

    Författare :Anirudh Venkat Chari; [2020]
    Nyckelord :Supervised learning; machine learning; product packaging; logistics; Övervakade inlärningsmodeller; förpackningslösning; logistik; maskininlärning;

    Sammanfattning : This thesis investigates the feasibility of supervised learning models in the decision-making problem to package products and predict an optimal packaging solution. The decision-making problem was broken down into a multi-class classification and a regression problem using relevant literature. LÄS MER