Essays about: "Automatiserad datamärkning"

Found 3 essays containing the words Automatiserad datamärkning.

1. 1. Duplicate detection of multimodal and domain-specific trouble reports when having few samples : An evaluation of models using natural language processing, machine learning, and Siamese networks pre-trained on automatically labeled data

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

   Author : Viktor Karlstrand; [2022]
   Keywords : Duplicate detection; Bug reports; Trouble reports; Natural language processing; Information retrieval; Machine learning; Siamese neural network; Transformers; Automated data labeling; Shapley values; Dubblettdetektering; Felrapporter; Buggrapporter; Naturlig språkbehandling; Informationssökning; Maskininlärning; Siamesiska neurala nätverk; Transformatorer; Automatiserad datamärkning; Shapley-värden;

   Abstract : Trouble and bug reports are essential in software maintenance and for identifying faults—a challenging and time-consuming task. In cases when the fault and reports are similar or identical to previous and already resolved ones, the effort can be reduced significantly making the prospect of automatically detecting duplicates very compelling. READ MORE

3. 2. Zero/Few-Shot Text Classification : A Study of Practical Aspects and Applications

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

   Author : Jacob Åslund; [2021]
   Keywords : zero-shot learning; few-shot learning; text classification; active learning; automated data labeling; interpretable machine learning; deep learning; NLP; NLU; zero-shot learning; few-shot learning; textklassificering; aktiv inlärning; automatiserad datamärkning; tolkningsbar maskininlärning; djupinlärning; NLP; NLU;

   Abstract : SOTA language models have demonstrated remarkable capabilities in tackling NLP tasks they have not been explicitly trained on – given a few demonstrations of the task (few-shot learning), or even none at all (zero-shot learning). The purpose of this Master’s thesis has been to investigate practical aspects and potential applications of zero/few-shot learning in the context of text classification. READ MORE

4. 3. Scalable Architecture for Automating Machine Learning Model Monitoring

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

   Author : Javier de la Rúa Martínez; [2020]
   Keywords : Model Monitoring; Streaming; Scalability; Cloud-native; Data Drift; Outliers; Machine Learning; Modellövervakning; Streaming-metod; Skalbarhet; Molnbaserad; Dataskift; Outlierupptäckt; Maskininlärning;

   Abstract : Last years, due to the advent of more sophisticated tools for exploratory data analysis, data management, Machine Learning (ML) model training and model serving into production, the concept of MLOps has gained more popularity. As an effort to bring DevOps processes to the ML lifecycle, MLOps aims at more automation in the execution of diverse and repetitive tasks along the cycle and at smoother interoperability between teams and tools involved. READ MORE