Toggle navigation
JUPYTER
FAQ
View as Slides
View as Code
Python 3 Kernel
View on Gist
Execute on Binder
Download Notebook
Notebook
Ten New Reasons to Use Jupyter
in Ten Minutes
¶
Peter Parente
IBM Emerging Internet Technology
1. Time-to-Value
¶
Interactive computing to help reduce accidental complexity in your workflow
2. Docker Stacks
¶
Opinionated stacks of ready-to-run Jupyter applications in Docker
3. Apache Toree
¶
Scala, Python, R Jupyter kernel for Apache Spark
4. Full-Text Search
¶
Search filenames, markdown, code to quickly locate past analyses
5. Dashboard Layout
¶
Put notebook output into a sharable dashboard layout for ease of interaction
6. Declarative Widgets
¶
Import and bind Polymer Web Components to functions and data
7. Notebooks as Web Apps
¶
Deploy dashboard-notebooks as standalone web applications
8. Notebook-Defined Web APIs
¶
Deploy annotated notebooks as HTTP microservices
9. Notebooks as Python Modules
¶
Import Python notebooks as Python modules and snippet libraries
10. Hosted Solutions
¶
Bonus: The Ecosystem
¶
Large and growing user and developer community
Links
¶
[1]
https://en.wikipedia.org/wiki/Cross_Industry_Standard_Process_for_Data_Mining
[2]
https://github.com/jupyter/docker-stacks
[3]
http://toree.incubator.apache.org/
[4,9]
https://github.com/jupyter-incubator/contentmanagement
[5]
https://github.com/jupyter-incubator/dashboards
[6]
https://github.com/jupyter-incubator/declarativewidgets
[7]
https://github.com/jupyter-incubator/dashboards_server
[8]
https://github.com/jupyter/kernel_gateway
[10]
https://bluemix.net
,
https://datascientistworkbench.com
[Bonus]
http://blog.ibmjstart.net/2016/03/21/powered-by-jupyter/
P.S.
¶
This
presentation
is a
notebook
available as a
gist
.