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• Proceedings of The 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 2023
• Supervised by Professor Danushka Bollegala, head of NLP and machine learning research group at the University of Liverpool
• Co-author: Yi Zhou

• Top 15% of the leaderboard globally by classifying potential disasters from extremely vague Twitter text dataset
• Text preprocessing, BERT word and sentence embedding, fine-tuning BERT

-> Database management and SQL, Applied AI (ML, DL), Math and Statistics for Data Science, Reinforcement learning and bioinspired optimization, Computational intelligence, Data mining and visualization, Object-oriented programing

-> MongoDB, Gensim, NLTK, TF-IDF word embedding, Latent Dirichlet Allocation

-> Object detection, Transfer learning, Raspberry Pi, IoT server, OpenCV

-> Hill Climb, Genetic algorithm, K-mean, H-clustering, Regression, Decision tree, Naïve Bayes classifier, CNN transfer learning

-> Transformer (BERT), Bi-directional LSTM, Time series analysis, Anomaly detection, Encoder-decoder (sequence to sequence), Text classification, Text summarization, Machine translation, Sentimental analysis, Named-entity recognition, Image augmentation, Image classification, Custom dataset preparation

-> EC2 instance, S3 Bucket, Amazon SageMaker

-> Pandas, Numpy, Matplotlib, Seaborn, Data visualization

-> HTML, Beautiful Soup, Selenium