to make all stages of ML smoother. You can customize your notebooks and compute resources to suit your data science needs. Multi-framework Jutopia provides support for PyTorch, TF, XGBoost, Keras and other environments. And support you to build a custom ML environment. Model Serving Jutopia is integrated with BentoML, an open-source framework for ML model serving, which package once and deploy anywhere, supporting Docker, K8s, Kuberflow, and more. Jupyter To Pipeline Architecture
managing ML workflows. A visual pipeline editor to design Airflow DAGs without knowing Python or learning Airflow primitives. Infrastructures Jutopia provides best-of-breed open-source systems as a service for ML, which will be deployed to diverse infrastructures such as Docker, Kubernetes, etc. Open Source Jutopia’s goal is not to rebuild other services, but we will expand open source projects and open source our excellent modules. Jupyter To Pipeline Architecture
Dataset Data exploration, Data preparation, Data validation, Productionalization Run code, Explore data, Present results https://netflixtechblog.com/notebook-innovation-591ee3221233
Web Context Different styles Jupyter_nb_viewer Easy to integrate Line Style https://github.com/line/devday_2020_jupyter_nb_viewer https://github.com/nteract/commuter https://linedevday.linecorp.co/2020/en/sessions/5342
Learning APIs Core Team Member Features Any ML frameworks Deploy anywhere High-Performance Central hub Modular and flexible https://github.com/bentoml/BentoML