Callisto: Brining Jupyter to Classroom
Amey Agrawal (~amey48) |
In recent years Python has fast gained acceptance as the preferred computing tool for academics across multiple domains, elevating its importance in classrooms. Jupyter, in particular, has proven its efficacy as an educational tool. However, setting up scientific Python environments can be troubling for newcomers, especially for those without prior programming experience. Further, it is exceedingly complicated for educators to evaluate graded components in Jupyter. In this poster, we would like to present Callisto, a tool we designed at BITS Pilani to improve the user experience for both educators and students using Jupyter in classrooms.
- Blog: https://agrawalamey.github.io/lessons-from-conducting-machine-learning-course-with-jupyter-notebooks/
- Demo: https://www.youtube.com/watch?v=fiKaIJcfsAs&feature=youtu.be
- Github: https://github.com/AgrawalAmey/callisto
Amey is a member technical staff in Qubole, where he works with Data Science and Spark teams. His primary area of research is log processing and he has been a key contributor to the state-of-the-art distributed log parser Delog. His other interests include reinforcement learning and representation learning.
Shrikant is a Computer Science graduate from BITS Pilani, the batch of 2018. He has over a year of experience working as a Software Engineer in Smartphone Camera Framework for Samsung Research, Bangalore. He was formerly a Project Intern at Robert Bosch Centre for Cyber-Physical Systems, IISc Bangalore working in IoT domain for the Smart City project.
- Github: https://github.com/AgrawalAmey
- LinkedIn: https://www.linkedin.com/in/agrawalamey
- Blog: https://agrawalamey.github.io/
- Github: https://github.com/shrikantsharda
- LinkedIn: https://www.linkedin.com/in/shrikantsharda/