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Livebook Alternatives
Similar projects and alternatives to livebook
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InfluxDB
Purpose built for real-time analytics at any scale. InfluxDB Platform is powered by columnar analytics, optimized for cost-efficient storage, and built with open data standards.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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explorer
Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
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Arraymancer
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
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awesome-advent-of-code
A collection of awesome resources related to the yearly Advent of Code challenge.
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interactive
.NET Interactive combines the power of .NET with many other languages to create notebooks, REPLs, and embedded coding experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better livebook alternative or higher similarity.
livebook discussion
livebook reviews and mentions
Posts with mentions or reviews of livebook.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-09-02.
- Apache Zeppelin
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Ruby in Jupyter Notebook
Definitely look into Livebook and Elixir, and the whole ecosystem around it, including:
- https://github.com/elixir-nx/axon Nx-powered Neural Networks
- https://github.com/elixir-nx/nx Multi-dimensional arrays (tensors) and numerical definitions for Elixir
- https://github.com/elixir-nx/scholar Traditional machine learning on top of Nx
- https://github.com/elixir-nx/bumblebee Pre-trained Neural Network models in Axon (+ Models integration)
- https://github.com/elixir-explorer/explorer Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
- https://fly.io/blog/rethinking-serverless-with-flame/ (for offloading large work to remote containers)
- https://www.youtube.com/watch?v=RABXu7zqnT0 InstructorEx
And of course Livebook (https://livebook.dev)
- Show HN: Adding Mistral Codestral and GPT-4o to Jupyter Notebooks
- Elixir Livebook 0.13
- Show HN: PlayBooks – Convert on-call documents into executable notebooks
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Elixir and Machine Learning in 2024 so far: MLIR, Arrow, structured LLM, etc.
I have always considered helping the community grow into a diverse ecosystem to be my main responsibility (the Python community being a great example here).
This particular effort started because some people got together and realized that we could do it! Do it in a way that felt part of Elixir and not just a bunch of bindings to C libraries.
We honestly never had the expectation that we had to beat Python (otherwise we would simply not have started). Early on, we were not even sure if we could be better at one single thing. However, 3 years later, we do have features that would be quite hard or impossible to implement in Python. For example:
* Nx Serving - https://hexdocs.pm/nx/Nx.Serving.html - allows you to serve machine learning models, across nodes and GPUs, with concurrency, batching, and partitioning, and it has zero dependencies
* Livebook - https://livebook.dev - brings truly reproducible workflows (hard to achieve in Python due to mutability), smart cells, and other fresh ideas
* A more cohesive ecosystem - Nx, Scholar, Explorer, etc all play together, zero-copy and all, because they are the only players in town
Of course, there are also things that Python can do, that we cannot:
* In Python, integration with C code is easier, and that matters a lot in this space. Python also allows C to call Python, and that's just not possible in the Erlang VM
* Huge ecosystem, everything happens in Python first
At the end of the day, what drives me is that the Erlang VM offers a unique set of features, and combining them with different problems have historically lead to interesting and elegant solutions. Which drives more people to join, experiment, run in production, and create new things.
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Super simple validated structs in Elixir
To get started you need a running instance of Livebook
- Arraymancer – Deep Learning Nim Library
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Setup Nx lib and EXLA to run NX/AXON with CUDA
LiveBook site
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Interactive Code Cells
I prefer functional programming with Livebook[1] for this type of thing. Once you run a cell, it can be published right into a web component as well.
[1] - https://livebook.dev
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A note from our sponsor - SaaSHub
www.saashub.com | 10 Sep 2024
Stats
Basic livebook repo stats
87
4,770
9.8
12 days ago
livebook-dev/livebook is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of livebook is Elixir.
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