Essays about: "Contextual Model of Learning"

Showing result 1 - 5 of 37 essays containing the words Contextual Model of Learning.

1. 1. Prevalent Discord. Exploring and estimating the prevalence of the type of user disagreement on news media Facebook posts discussing the Colombian peace process (2020-2022)

   University essay from Lunds universitet/Graduate School

   Author : Luis Felipe Villota Macias; [2024]
   Keywords : Agonistic peace; antagonism; big data analytics; binary logistic regression; computational content analysis; Colombia; Colombian peace process; discord; Facebook; machine learning; peace process; public opinion and sentiment; social media; Law and Political Science; Social Sciences;

   Abstract : This thesis is dedicated to exploring and understanding public reactions within negotiated peace settlements based on social media data. Concretely, to modeling public opinion and sentiment within the context of the Colombian peace process using a curated dataset of N= ~1. READ MORE

3. 2. Collaborative Learning in an Immersive Virtual Environment: The Effects of Context and Retrieval Practice

   University essay from Lunds universitet/Institutionen för psykologi

   Author : Noelle Bender; [2024]
   Keywords : VR; collaborative Mapping; retrieval practice; contextual variation; desirable difficulty; ecological validity; Social Sciences;

   Abstract : The accessibility of Virtual Reality (VR) enables the investigation of desirable difficulties originating from memory research with increased ecological validity. The two desirable difficulties include contextual variation and retrieval practice. READ MORE

4. 3. An Empirical Survey of Bandits in an Industrial Recommender System Setting

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Tobias Schwarz; Johan Brandby; [2023-09-21]
   Keywords : computer science; industrial application; machine learning; reinforcement learning; multi-armed bandits; MAB; contextual multi-armed bandits; survey; batch learning;

   Abstract : In this thesis, the effects of incorporating unstructured data—images in the wild—in contextual multi-armed bandits are investigated, when used within a recommender system setting, which focuses on picture-based content suggestion. The idea is to employ image features, extracted by a pre-trained convolutional neural network, and study the resulting bandit behaviors when including respective excluding this information in the typical context creation, which normally relies on structured data sources—such as metadata. READ MORE

5. 4. Contextual short-term memory for LLM-based chatbot

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Mikael Lauri Aleksi Törnwall; [2023]
   Keywords : Chatbot; Artificial Intelligence; Machine Learning; Language Model; Large Language Model; GPT-3; Natural Language Processing; Text Summarization; Dialogue Summarization; Prompt Design; Prompt Programming; Chatbot; Artificiell Intelligens; Maskininlärning; Språkmodell; Stor Språkmodell; GPT-3; Naturlig Ppråkbehandling; Textsammanfattning; Sammanfattning av Dialog; Design för Inmatningsprompt; Inmatningsprompt Programmering;

   Abstract : The evolution of Language Models (LMs) has enabled building chatbot systems that are capable of human-like dialogues without the need for fine-tuning the chatbot for a specific task. LMs are stateless, which means that a LM-based chatbot does not have a recollection of the past conversation unless it is explicitly included in the input prompt. READ MORE

6. 5. Analysing the possibilities of a needs-based house configurator

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Roman Ermolaev; [2023]
   Keywords : Needs-based; Configurator; House configurator; CNN; BERT; DistilBERT; Swedish;

   Abstract : A needs-based configurator is a system or tool that assists users in customizing products based on their specific needs. This thesis investigates the challenges of obtaining data for a needs-based machine learning house configurator and identifies suitable models for its implementation. READ MORE