TornadoVM
ydata-profiling
TornadoVM | ydata-profiling | |
---|---|---|
22 | 43 | |
1,120 | 12,070 | |
1.4% | 1.1% | |
9.9 | 8.5 | |
1 day ago | 4 days ago | |
Java | Python | |
Apache License 2.0 | MIT License |
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.
TornadoVM
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Intel Gaudi 3 AI Accelerator
You don't need to use C++ to interface with CUDA or even write it.
A while ago NVIDIA and the GraalVM team demoed grCUDA which makes it easy to share memory with CUDA kernels and invoke them from any managed language that runs on GraalVM (which includes JIT compiled Python). Because it's integrated with the compiler the invocation overhead is low:
https://developer.nvidia.com/blog/grcuda-a-polyglot-language...
And TornadoVM lets you write kernels in JVM langs that are compiled through to CUDA:
https://www.tornadovm.org
There are similar technologies for other languages/runtimes too. So I don't think that will cause NVIDIA to lose ground.
- Java VectorAPI compatiblity with TornadoVM GPU programming framework
- Java GPU pre/post processing with ONNX RT and TornadoVM
- FLaNK Stack 05 Feb 2024
- FLaNK 25 December 2023
- GPU Acceleration for Python, JavaScript, Ruby from Java with Truffle
- TornadoVM v1.0 Released
- TornadoVM 1.0
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From CPU to GPU and FPGAs: Supercharging Java Applications with TornadoVM [video]
Presented by Juan Fumero, PhD & Research Fellow (The University of Manchester, UK) during the JVM Language Summit 2023 (Santa Clara CA).
More information on TornadoVM can be found at https://www.tornadovm.org/
Tags: #Java #JVMLS #GPU #FPGA #OpenJDK #GraalVM #AI
ydata-profiling
- FLaNK 25 December 2023
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First 15 Open Source Advent projects
6. Ydata-synthetic and Ydata-profiling by YData | Github | tutorial
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Coding Wonderland: Contribute to YData Profiling and YData Synthetic in this Advent of Code
Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!
- Data exploration is not dead
- Explore your data in a single line of code
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Which preprocessing steps to improve the performance of a naive bayes classifier
My suggestion start with the EDA - there are a lot of packages that automate that for you already. My usual go-to: https://github.com/ydataai/ydata-profiling.
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Simulating sales data
If you're not sure about the behaviour of your data (i.e., if the original data has properties like seasonality), you can use ydata-profiling to profile your data first.
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I recorded a Data Science Project using Python and uploaded it on Youtube
Super cool! For EDA, you could give ydata-profiling a spin sometime and speed up the process!
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Ydata-Profiling and Dask
Hey guys,
We've been recently at the Dask Demo Day and we're hoping to launch a new feature on ydata-profiling, with the support for Dask dataframes!
We're looking for Dask Wizards to start collaborating on this feature, so if you're interested, please join us to define the roadmap of the project and start making it real
Current GitHub branch is here: https://github.com/ydataai/ydata-profiling/tree/feat/dask
Dedicated dask channel here: https://discord.gg/EHDBuSSDuy
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🧠 ydata-profiling + Dask!
We're looking for Dask Wizards 🧙🏻♂️ to start collaborating on this branch, so if you're interested, please join us to define the roadmap of the project and start making it real 🚀
What are some alternatives?
Aparapi - The New Official Aparapi: a framework for executing native Java and Scala code on the GPU.
dtale - Visualizer for pandas data structures
openapi4j - OpenAPI 3 parser, JSON schema and request validator.
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
GraalVMREPL - REPL (read–eval–print loop) shell built on top of JavaFX and GraalVM stack, incorporating GraalJS, GraalPython, TruffleRuby and FastR
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
kattlo-cli - Kattlo CLI Project
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
junodb - JunoDB is PayPal's home-grown secure, consistent and highly available key-value store providing low, single digit millisecond, latency at any scale.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
jr - JR: streaming quality random data from the command line
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b