nbestimate VS IRkernel

Compare nbestimate vs IRkernel and see what are their differences.

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nbestimate IRkernel
1 5
82 1,625
- 0.6%
9.5 0.0
8 days ago 21 days ago
Jupyter Notebook Jupyter Notebook
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

nbestimate

Posts with mentions or reviews of nbestimate. We have used some of these posts to build our list of alternatives and similar projects.

IRkernel

Posts with mentions or reviews of IRkernel. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-07.

What are some alternatives?

When comparing nbestimate and IRkernel you can also consider the following projects:

awesome-notebooks - A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.

pre-commit-jupyter - Clean up cell outputs of jupyter notebook

graph-notebook - Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.

learn-you-a-haskell-notebook - Jupyter adaptation of Learn You a Haskell for Great Good!

homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

ocaml-jupyter - An OCaml kernel for Jupyter (IPython) notebook

py - Repository to store sample python programs for python learning

Kalman-and-Bayesian-Filters-in-Python - Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.