Abiodun Modupe poses moderate experience with Machine Learning, especially in relation to data analytics and natural language processing. She currently work in CSIR – A data science research group using tools such Natural Language Processing (NLP), Machine Learning and Deep Learning Framework e.g., Keras with tensorflow backend.
She’s worked on a deep-learning architecture paper named ACNN-LSTM, which combines asymmetric convolutional neural networks (ACNN) with a long short-term memory (LSTM) network to learn new features and representing useful information (embedded in conversational messages posted to online social media) for all kinds of classification tasks. The research trained the model on thousands of randomly selected English-language short text samples. Experimental results demonstrate that the model significantly outperforms state-of-the-art methods with the propose semi-supervised learning for semantic classification. The implementation result and code on the paper is online (github.com/dupsys) for public comment and used. No one did the work with me.