Machine Learning at Berkeley
Building and fostering a vibrant machine learning community
Machine Learning at Berkeley (ML@B) is a student-run organization dedicated to fostering a vibrant machine learning community on the UC Berkeley campus by providing educational and computational resources to undergraduate and graduate students.
We empower passionate students of all backgrounds and skill levels to solve real world data-driven problems in both academic research and industry settings through collaboration with companies and internal research.
By growing a strong machine learning community at UC Berkeley, we hope to benefit, educate, and inspire the students at the university as well as aiding the machine learning community at large.
Industry: Machine Learning at Berkeley's consulting branch allows members to work together with companies to tackle challenging real world problems with the use of machine learning and data science. Each consulting project consists of around 8-10 members and lasts one semester. Through the ML@B consulting projects, members gain the experience to solve machine learning and data science problems in industry.
Machine Learning at Berkeley's research division seeks to provide a platform for students and faculty to collaborate outside of the context of the many AI/ML research laboratories at Berkeley. We believe that landmark research in machine learning almost always comes from left field, and we cherish and encourage novelty in our division.
Our projects and papers are proposed by students and then backed over the course of each academic year into fully fledged research teams. The proposal process leads to a diverse group of projects each year exploring areas from deep reinforcement learning to statistical machine learning, harnessing the creativity and unique backgrounds of our members.