Sökning: "machine learning"

Visar resultat 1 - 5 av 4533 uppsatser innehållade orden machine learning.

  1. 1. "The Uphill AI Contract Challenge The Intra-Active Task: Reimagining Contracts"

    Magister-uppsats, Göteborgs universitet/Juridiska institutionen

    Författare :Filip Seiborg Wikström; [2024-02-16]
    Nyckelord :AI; Contract Law; New Materialism; Karen Barad; Intra-Action; Spacetimemattering; Ethico-Onto-Epistem-Ology; Cartesian-Newtonian paradigms; Antimethodology; Agency; Machine Learning;

    Sammanfattning : The traditional contract theories are insufficient to handle the challenges Artificial Intelligence (AI) is currently causing and will continue to cause to contract law. These challenges involve problems concerning the subject/object divide, agency, the embedding of legal code into interactive programming code, and ethical aspects concerning the transfer of power away from lawyers. LÄS MER

  2. 2. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Habib Jabeli; [2024]
    Nyckelord :Machine Learning; Flight Comparison; Flygresor.se; Neural Networks; Flight Ranking; Random Forest; XGBoost;

    Sammanfattning : Flygresor.se, a leading flight comparison platform, uses machine learning to rankflights based on their likelihood of being clicked. The main goal of this project was toimprove this flight sorting to obtain a better user experience. The platform's existingmodel is based on a neural network approach and a limited set of features. LÄS MER

  3. 3. Cross project Just-In-Time bug detection

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

    Författare :Axel Pettersson; [2024]
    Nyckelord :JITLine; Bug detection; Software Development; JITLine; Bugg identifiering; Mjukvaruutveckling;

    Sammanfattning : Software is present in almost all aspects of our lives, and with more parts of life beingdriven by code, the importance of limiting bugs is critical. Studies have shown that thelonger a bug is present in a system increases the complexity of finding and handlingthe bug. LÄS MER

  4. 4. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Nikolaos Staikos; [2024]
    Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER

  5. 5. ML implementation for analyzing and estimating product prices

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

    Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
    Nyckelord :Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

    Sammanfattning : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. LÄS MER