"artificial intelligence" - Selaus asiasanan mukaan Yrkeshögskolan Arcada
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Artificial Intelligence for Email Personalization
(2024)This thesis explores the integration and impact of Artificial Intelligence (AI) on email personalization. Utilizing a qualitative approach through structured interviews with marketing professionals, the study investigates ... -
Artificial Intelligence in digital marketing: now and in the future
(2021)This is a study conducted in the field of digital marketing with the usage of AI, the aim of the study was to find the impact that AI currently has on digital marketing and what it could look like in the future. The structure ... -
Artificial intelligence in the Financial Services industry : A study of future opportunities and risks
(2024)The use of Artificial Intelligence (AI) in the financial services (FS) industry has transformed financial services and processes significantly in recent years. This thesis aims to unravel what future opportunities and risks ...Rajoitettu käyttöoikeus / Restricted access / Tillgången begränsad -
Artificial Intelligence: An analysis of perceptions of the impact of AI on the financial labour market
(2020)AI technology has become increasingly prevalent within the finance sector and undeniably, the impact of AI has been revolutionary and will continue to progress and become the basis of multiple innovative ideas and technologies. ... -
Car sales analysis in the Nordic Countries
(2023)Sales forecasting is an essential component of business intelligence and, artificial intelligence and predictive analytics are now essential tools for companies to predict market trends and forecast sales volumes. In ... -
Control of Robots
(2023)The efficiency of modern manufacturing relies on industrial robots which are programmed to perform a number of different tasks that were previously done by humans. This thesis explores the possibilities of control of robots, ... -
Data-Driven Modelling of Gas Turbine Engines
(2021)This study investigates and compares linear and nonlinear data-driven models of a gas turbine engine. These linear models consist of Ridge, Lasso, and Multi-Task Elastic-Net models, which are set up based on linear ... -
Edge MLOps framework for AIoT applications
(2020)Recent years witnessed a boom in IoT devices resulting in big data and demand for low latency communication giving rise to a demand for 5G Networks. This shift in the infrastructure is enabling real-time decision making ... -
Enhancing Customer feedback processing with Machine Learning in Microsoft Azure
(2022)Text Classification and Natural Language Processing (NLP) is developing fast, and all the applications are rapidly evolving, GPT-3 emerged in the field just last year and there are some open-source options in the field, ... -
Examination of air pollutant concentrations in Smart City Helsinki using data exploration and deep learning methods
(2021)Air quality has become a major concern for most of the cities around Europe due to rapid urbanization and industrialization. Smart City is an initiative to solve such problems by integrating information and communication ... -
Explainability of time series models
(2022)The lack of interpretability of machine learning models is a drawback of their use. To better understand how the model works, how data affects its performance, how the model could be improved, and to gain trust in the ... -
Exploring Success Factors in Chatbot Implementation Projects
(2019)Chatbots are digital agents which can be used to automatize an organization’s customer interactions and internal business processes. This conversational software is powered by artificial intelligence and utilizes natural ... -
Glaucoma in the era of AI : Exploring the current state, challenges and opportunities of AI-driven solutions in glaucoma care
(2024)Artificial intelligence (AI) is widely considered nowadays as one of the most innovative technologies of the 21st century, set to revolutionize every existent industry and transform the way how we live. AI have also been ...Rajoitettu käyttöoikeus / Restricted access / Tillgången begränsad -
How AI can help forecasting in purchasing
(2024)Since the industrial revolution, there has been notable progress in technological innovation, leading to the transformation of many manual tasks and processes that had previously been limited by human physical capabilities ... -
How can financial institutions more efficiently prevent credit-card fraud and AML using AI and machine learning technologies?
(2021)As society and payments are getting increasingly digitized and most of financial transactions are done by credit-card or wire-transfer, the focus on financial crime, fraud and Anti-Money Laundering is becoming a focus point ... -
Improving Customer Service Efficiency Using Generative Artificial Intelligence
(2024)Social media has presented customer relationship management with a challenge while providing companies with a tool to maintain their relationships with customers. Effort and time in processing customers’ feedback may ... -
Intelligent Automation in Journalism: Are newsrooms ready to let machines write our news?
(2022)The advancements in readily available structured data, artificial intelligence and automation tools have led to newsrooms exploring the possibility of creating news articles automatically. Sports, finance, politics and ... -
Machine Learning methods for classification of Acid Sulfate soils in Virolahti
(2020)Acid Sulfate (AS) soils are among the most dangerous soils naturally occurring soils. This is due to the several ecological damages that they can generate. In Europe, the highest concentration of this type of soils is ... -
Open-source dog breed identification using CNN: explanation of the development & underlying technological specifications
(2023)This thesis aims to develop a deep learning model that uses the Fast.ai library and transfer learning to create a convolutional neural network model. The model will identify dog breeds in digital images and evaluate the ... -
Reinforcement Learning for Financial Portfolio Management: A study of Neural Networks for Reinforcement Learning on currency exchange market
(2021)Portfolio management is the process of continually reallocating funds into financial instruments, aiming to maximize the return. This paper presents a Reinforcement Learning framework where an agent interacts with the ...

















