Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Join us to experiment, break things, and imagine new possibilities. Data Club meetings are meetings, not workshops. An introduction to a bit of software is followed by opportunities to try the ...

In order to be successful in this course, you will need to know how to program in Python. The expectation is that you have completed the first three courses in this Applied Data Science with Python ...

A Streamlit-based job offer application featuring interactive visualizations and chatbot/Q&A bots powered by MistralAI Mixtral-8x7B LLM, with offers stored in a SQLite data warehouse and Dockerised ...

Abstract: This study seeks to harness the power of big data through text mining the content of publicly available YouTube tutorials related to Electronic Health Record (EHR) systems. Most information ...

ABSTRACT: Semi-supervised Support Vector Machines is an appealing method for using unlabeled data in classification. Smoothing homotopy method is one of feasible method for solving semi-supervised ...