Notebooks are great for prototyping, longer pipelines or processes.
If you are a user of PyCharm or Jupyter Notebook and an exploratory data scientist, I would encourage you to switch you to Jupyter Lab.
For Jupyter Lab installation steps go here
Below are some of the advantages that I see using Jupyter Lab over Jupyter Notebook:-
- The new terminal is a tab view to use compared.
- The ability to set out multiple windows easily, much like an IDE
- This will make working on a remote server so much nicer, just start Jupyter Lab and an ssh tunnel and you have a terminal plus notebooks.
- Remote server file editors in one browser window.
I have recommendations below for Jupyter notebook team and hoping would be present in JupyterLab 1.0:-
- I do miss though is good separation between code and data, it is a pain when someone just takes a look at your notebook and it autosaves, the code block counters reset, this alters the file. I can see the benefits of stuffing everything into a single file, but separating would be so much better.
- Also stuffing everything into a single file helps in version control too.
- If it is possible to plot interactive matplotlib plots (for getting mouseover values zooming etc).
JupyterLab 1.0 is planned for the end of 2018 and hoping for JupyterLab 1.0 will eventually replace the classic Jupyter Notebook.
If you are notebook lover then there are other options also available for Machine Learning tools and stuff:-
Google colabs(Free GPU): If you are Google fan then you have Google colabs(Free GPU) which is more like Juypter and has a google-docs style juypter notebook that’s quite good. Yes you can connect your GPU for machine learning. You can see more about Google colabs at https://colab.research.google.com/notebook.
Azure Notebooks: Azure Notebooks is also promising but without the support of GPU, you can see more about Azure Notebooks at https://notebooks.azure.com/
R Notebooks: I am not using R Notebooks but i saw some advantages over using R Notebook compare to Jupyter Notebook, see more at http://minimaxir.com/2017/06/r-notebooks/
Congratulations to Jupyter Lab Team!
Happy Machine Learning…