Discussion Forums

Machine Learning and Science Forum

The BIDS Machine Learning and Science Forum (originally the Berkeley Statistics and Machine Learning Forum) was launched in Spring 2018 and currently meets biweekly (during the spring and fall semesters) to discuss current applications across a wide variety of research domains in the physical sciences and beyond. These active sessions bring together domain scientists, statisticians, and computer scientists who are either developing state-of-the-art methods or are interested in applying these methods in their research. This Forum is hosted by BIDS Faculty Affiliate...

Data Science By Design (DSxD)

Data Science By Design (DSxD) is a community of practice to curate ideas about data narratives, innovative communication approaches and aesthetic visual design principles. This project aims to conscientiously develop the future of data science with diversity, inclusion, and open education as guiding principles that incorporate transparent research practices and accessible training. Our events and resources will empower and support attendees to produce visual content that effectively and artfully communicates the practice of data science research in the form of how-to...

Best Practices in Data Science

The BIDS Best Practices in Data Science forum focuses on increasing diversity and inclusivity in Berkeley’s active data science community. This discussion series, which launched in Spring 2019, meets to synthesize participants' experiences working in the field of data science, discern how data science practices can be done well, and discover how to improve upon lessons-learned. Discussions are led by BIDS Biology and Environmental Sciences Lead Ciera C. Martinez and discussions cover a broad range of meta-research topics — including ethics,...

Information and Uncertainty in Data Science ~ Discussion Forum

The BIDS 'Information and Uncertainty in Data Science' Discussion Forum is a forum for open inquiry and discussion about a wide range of recurring data science fundamentals, including information, uncertainty, entropy, bits, probability, machine learning, generalization, and others. Led by BIDS Faculty Affiliate Gerald Friedland, the group facilitates academic discourse on the practical use of the fundamental concepts across a wide variety of research disciplines, and strives for clarity and understanding using real-world scenarios, visual examples,...