This workshop covers dataset preprocessing, encoding categorical variables, handling NaN values, and preparing data for machine learning in Python. Instructors will also go over F1 score, which is the metric used to evaluate participants.
Datathon tutorial, dataset preprocessing, encoding categorical variables, handling NaN values, preparing data for machine learning in Python.
Keerthi Gopalakrishnan explores Multi-Armed Bandit and Contextual Bandit algorithms for optimizing online recommendations and balancing exploration with exploitation.
Claudia Perlich, Managing Director at Two Sigma, joins co-host Margot Gerritsen, WiDS co-founder and Stanford Professor Emerita, to discuss biases in AI and responsible machine learning. Claudia also shares career insights on curiosity, scientific thinking, and communication in data science.
Huda Nassar joins co-host Margot Gerritsen to explore how the fusion of mathematics and computer science drives real-world innovation. They dive into Huda’s journey from earning her PhD at Purdue to developing advanced graph algorithms at RelationalAI, the pivotal role of mentorship, and why she champions the Julia programming language.
Hannah Pham, Head of Data Science, Consumers at Pinterest, shares how her immigrant experience shaped her career, emphasizing the importance of language learning, understanding problems in data science, and people development. She also discusses burnout, flexible work environments for women, and evolving opportunities in the field.
Watch this WiDS Workshop where data science professionals Jie Z. Nissel and Elizabeth Johnson share their journeys from STEM to data science.
This conversation covers career growth and balance, transitioning to leadership, and how self-awareness can guide success.
In this talk, Rachita Naik shares her journey and experiences as a Machine Learning Engineer at Lyft, detailing the path that led her to pursue a career in the field.
Sydney Hazen, a Privacy Data Scientist at Ford, shares her journey from a college intern to a full-time role. She highlights how internships can lead to job offers and the importance of real-world experience and corporate navigation.
Karin Golde discusses the rise of large language models like ChatGPT, highlighting their popularity, challenges, and the need for diverse perspectives in AI development, while sharing her experiences and advising women in leadership roles.
Allison Koenecke, currently a postdoc at Microsoft Research and soon to be assistant professor at Cornell, discusses her decision to pursue a career in academia focused on algorithmic fairness and causal inference in public health.
Karina Edmonds, Global Head of Academies and University Alliances at SAP, has spent her career building bridges between business and academia. She is passionate about promoting fairness in data science by bringing more young people, women, and underrepresented groups into the field.
Marzyeh Ghassemi, an assistant professor at the University of Toronto, is focused on Healthy ML—applying machine learning to understand and improve health.
Hear stories of women in data science from around the Globe!
Becki Cook: Brisbane, Australia
Staying Connected Through Community Outreach
Philomena Mbura: Nairobi, Kenya
Finding Work/Life Balance
Amanda Milberg: Colorado, USA
Building a Supportive Network