Sökning: "Deep learning"

Visar resultat 1 - 5 av 2058 uppsatser innehållade orden Deep learning.

  1. 1. 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

  2. 2. 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

  3. 3. Hur användandet av samtal och diskussion påverkar mellanstadieelevers förståelse för matematik

    Uppsats för yrkesexamina på grundnivå, Malmö universitet/Institutionen för naturvetenskap, matematik och samhälle (NMS)

    Författare :Rasmus Schultz; Lukas Scherp; [2024]
    Nyckelord :conversation; discussion; interaction; leading classroom discussions; learning Strategies; mathematics; mathematics teaching; mathematical concept; middle school; using conversation; vocabulary;

    Sammanfattning : This research overview is an evaluation of knowledge and explores the impact of language linked to mathematics. This particularly in the context of conversations and discussions, on the mathematical understanding of students in the ages between ten to twelve years old. LÄS MER

  4. 4. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Sofia Leksell; [2024]
    Nyckelord :Federated Learning; Adversarial Attacks; Regression; Classification;

    Sammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving  a noticeable gap in FL research specifically for regression models. LÄS MER

  5. 5. Learning a Grasp Prediction Model for Forestry Applications

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Elias Olofsson; [2024]
    Nyckelord :Forwarder; Autonomous grasping; Deep learning; Multibody dynamics; Convolutional neural network;

    Sammanfattning : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. LÄS MER