JupyterLab Now Available

Project Jupyter announces the general availability of JupyterLab:

JupyterLab is an interactive development environment for working with notebooks, code and data. Most importantly, JupyterLab has full support for Jupyter notebooks. Additionally, JupyterLab enables you to use text editors, terminals, data file viewers, and other custom components side by side with notebooks in a tabbed work area.

JupyterLab provides a high level of integration between notebooks, documents, and activities:

  • Drag-and-drop to reorder notebook cells and copy them between notebooks.

  • Run code blocks interactively from text files (.py, .R, .md, .tex, etc.).

  • Link a code console to a notebook kernel to explore code interactively without cluttering up the notebook with temporary scratch work.

  • Edit popular file formats with live preview, such as Markdown, JSON, CSV, Vega, VegaLite, and more.

I like this, as I’m a big fan of notebooks but sometimes you just want to write some diagnostic queries and an IDE is way better for that. H/T Giovanni Lanzani

Related Posts

Building an Image Classifier with PyTorch

Rogier van der Geer shows how you can use PyTorch to build out a Convolutional Neural Network for image classification: The tool that we are going to use to make a classifier is called a convolutional neural network, or CNN. You can find a great explanation of what these are right here on wikipedia. But we […]

Read More

xgboost and Small Numbers of Subtrees

John Mount covers an interesting issue you can run into when using xgboost: While reading Dr. Nina Zumel’s excellent note on bias in common ensemble methods, I ran the examples to see the effects she described (and I think it is very important that she is establishing the issue, prior to discussing mitigation).In doing that I ran into one more […]

Read More

Categories

February 2018
MTWTFSS
« Jan Mar »
 1234
567891011
12131415161718
19202122232425
262728