<p>Feel the cool breeze of Autumn R Ladies. Come and meet us because we have two speakers excited to share their research about the application of Big Data and Machine Learning in their respective field.</p> <p>Our first speaker is Joji Teves, a current Ph.D. fellow at the University of Copenhagen – iMED program. As a trained cellular biologist in a computational biology group, Joji is currently exploring big data tools to map out genomic marks of healthy and diseased cell states. Prior to moving to Copenhagen, Joji earned her Master’s at the University of Arizona College of Medicine, USA where she studied Patient-derived biospecimens from Parkinson’s disease patients and studied cellular marks related to cellular autophagy and UV damage in comparison to healthy age-match cohorts. As a “data science” noob, she takes on a different perspective on how data science tools can be applied in biology to study health and diseases.</p> <p>Our second speaker is Jhaz Petersen - a data-savvy Marketer who is a Graduate from Copenhagen Business School. She studied the traditional research methodologies but wanted to challenge that with the current technologies available. Therefore, she applies Machine Learning Algorithms in analyzing Big Data to solve Sales and Marketing case problems. She would like to share her original framework on how businesses in every industry can leverage their existing big data to create a business strategy.</p> <p>Program:<br/>17:00 - 17:15 Welcome<br/>17:15 - 17:35 Presentation by Joji Marie Teves - "Exploring Computational<br/>Biology to study Cellular Health and Disease"<br/>17:35 - 17:45 BREAK<br/>17:45 - 18:05 Presentation by Jhaz Petersen - "Leveraging Big Data and Machine Learning in Sales &amp; Marketing - Application of Market Basket Analysis, Clustering &amp; 3D Customer Segmentation in R"<br/>18:05 - 18:30 Closing and Networking</p> <p>Coffee and snacks will be served.</p> <p>Stay tuned for more details.</p> <p>*New info: If you are interested to learn the codes, I can share it after the presentation. Email me at [masked]. Due to time constraints, I will not be able to explain the codes and the steps line by line but you can practice the code on your own time with your own dataset.</p> <p>Kind regards,</p> <p>R Ladies CPH</p>