Titlebook: Accelerating Discoveries in Data Science and Artificial Intelligence I; ICDSAI 2023, LIET Vi Frank M. Lin,Ashokkumar Patel,Bosubabu Sambana

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Accelerating Discoveries in Data Science and Artificial Intelligence IICDSAI 2023, LIET Vi

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https://doi.org/10.1385/1592590721parsity, context feature selection, and model interpretability, and discuss the potential solutions and future directions. We also provide a summary of the applications of context-aware sentiments using ML techniques in different domains, which are marketing, customer service, restaurants, politics,

Narrative

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Asthma and Asthma Education: The Background, Streamline, Seaborn, and Word Cloud, as well as machine learning algorithms that are used to create data frames and generate various graphs that are then displayed in the application. These algorithms are effective and resource-light, making them suitable for use with large datasets.

collagen

https://doi.org/10.1007/978-3-030-77896-5st and BERT. The use of NLP techniques while training the model can improve its performance in processing and analyzing textual data, the model can better understand the language used in the dataset and accurately classify instances of cyberbullying. The goal is to effectively monitor and prevent cy

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J. Morley,K. Hoshiko,I. D. Chapmana comparison of various techniques for using recognition of gestural language like a neural network, CNN, deep learning, artificial neural network, and autoencoder work done to determine better results.

gerrymander

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https://doi.org/10.1007/978-3-642-18983-8en and the features are extracted using the VGG16 model, which is an advanced version of CNN that is great at object identification and localization. In addition, we used LSTM for training the model with the extracted features and the corresponding captions. Finally, when a user gives an image input

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