Sökning: "Online supervised learning"

Visar resultat 1 - 5 av 40 uppsatser innehållade orden Online supervised learning.

1. 1. Effectivisation of keywords extraction process : A supervised binary classification approach of scraped words from company websites

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Josef Andersson; Max Fremling; [2023]
   Nyckelord :Machine learning; keyword classification; unbalanced data; word embedding;

   Sammanfattning : In today’s digital era, establishing an online presence and maintaining a well-structured website is vitalfor companies to remain competitive in their respective markets. A crucial aspect of online success liesin strategically selecting the right words to optimize customer engagement and search engine visibility. LÄS MER

3. 2. Sentimental Analysis of CyberbullyingTweets with SVM Technique

   Kandidat-uppsats,

   Författare :Hrushikesh Thanikonda; Kavya Sree Koneti; [2023]
   Nyckelord :Cyberbullying tweets; Dataset; Data preprocessing; Machine Learning; Supervised Learning; Support Vector Machine; Validation.;

   Sammanfattning : Background: Cyberbullying involves the use of digital technologies to harass, humiliate, or threaten individuals or groups. This form of bullying can occur on various platforms such as social media, messaging apps, gaming platforms, and mobile phones. With the outbreak of covid-19, there was a drastic increase in utilization of social media. LÄS MER

4. 3. An unsupervised method for Graph Representation Learning

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

   Författare :Yi Ren; [2022]
   Nyckelord :Graph Representation Learning; unsupervised learning; machine learning;

   Sammanfattning : Internet services, such as online shopping and chat apps, have been spreading significantly in recent years, generating substantial amounts of data. These data are precious for machine learning and consist of connections between different entities, such as users and items. LÄS MER

5. 4. Online Unsupervised Domain Adaptation

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

   Författare :Theodoros Panagiotakopoulos; [2022]
   Nyckelord :Unsupervised Domain Adaptation; Continual Learning; Curriculum Learning; Clear2Rain; Self-Supervised Learning; Semantic Segmentation; Transfer Learning; Online Learning; Unsupervised Domain Adaptation; Kontinuerligt lärande; Curriculum Learning; Clear2Rain; Self-Supervised Learning; Semantisk Segmentering; Transfer Learning; Online Learning;

   Sammanfattning : Deep Learning models have seen great application in demanding tasks such as machine translation and autonomous driving. However, building such models has proved challenging, both from a computational perspective and due to the requirement of a plethora of annotated data. LÄS MER

7. 5. Continual Learning and Biomedical Image Data : Attempting to sequentially learn medical imaging datasets using continual learning approaches

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

   Författare :Davit Soselia; [2022]
   Nyckelord :Deep Learning; Continual Learning; Catastrophic Forgetting; Biomedical Image Classification; Djup inlärning; kontinuerligt lärande; katastrofal glömska; biomedicinsk bildklassificering;

   Sammanfattning : While deep learning has proved to be useful in a large variety of tasks, a limitation remains of needing all classes and samples to be present at the training stage in supervised problems. This is a major issue in the field of biomedical imaging since keeping samples in the training sets consistently is often a liability. LÄS MER