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CUDA VS Open Data Hub

Compare CUDA VS Open Data Hub and see what are their differences

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CUDA logo CUDA

Select Target Platform Click on the green buttons that describe your target platform.

Open Data Hub logo Open Data Hub

OpenDataHub
  • CUDA Landing page
    Landing page //
    2023-05-23
  • Open Data Hub Landing page
    Landing page //
    2023-06-01

CUDA videos

+ Add

1971 Plymouth Cuda 440: Regular Car Reviews

More videos:

  • Review - Jackson Kayak Cuda Review
  • Review - Great First Effort! The New $249 Signum Cuda

Open Data Hub videos

+ Add

Open Data Hub Introduction

More videos:

  • Review - Fraud Detection Using Open Data Hub on Openshift
  • Review - Installing Open Data Hub on OpenShift 4.1

Category Popularity

0-100% (relative to CUDA and Open Data Hub)

CUDA

Open Data Hub

Data Science And Machine Learning
82 82%
Data Science And Machine Learning
18% 18
AI
100 100%
AI
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100
Business & Commerce
100 100%
Business & Commerce
0% 0

User comments

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Social recommendations and mentions

Based on our record, CUDA seems to be a lot more popular than Open Data Hub. While we know about 36 links to CUDA, we've tracked only 3 mentions of Open Data Hub. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

CUDA mentions (36)

  • A comprehensive guide to running Llama 2 locally
    For my fellow Windows shills, here's how you actually build it on windows: Before steps: 1. (For Nvidia GPU users) Install cuda toolkit https://developer.nvidia.com/cuda-downloads 2. Download the model somewhere: https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/resolve/main/llama-2-13b-chat.ggmlv3.q4_0.bin In Windows Terminal with Powershell: 
        git clone https://github.com/ggerganov/llama.cpp.
    - Source: Hacker News / 10 months ago
  • Nvidia with linux....... not a good combination
    I use Ubuntu and configuring nvidia drivers is very easy installing from here https://developer.nvidia.com/cuda-downloads. Source: 10 months ago
  • Can't get CLBLAST working on oobabooga
    You have posted almost no information about your Hardware and what exactly you have done. Do you actually have NVIDIA? Have you actually installed CUDA? Also when exactly do you get the error, while installed the python package or later? Source: 10 months ago
  • NEW NVIDIA 535.98 DRIVER!!- INCREASE SPEED, POWER, IMAGE SIZE AN WHO KNOW WHAT ELSE MORE!
    EDIT: LINK TO CUDA-toolkit: https://developer.nvidia.com/cuda-downloads. Source: 11 months ago
  • WizardLM-30B-Uncensored
    It's worth noting that you'll need a recent release of llama.cpp to run GGML models with GPU acceleration here is the latest build for CUDA 12.1), and you'll need to install a recent CUDA version if you haven't already (here is the CUDA 12.1 toolkit installer -- mind, it's over 3 GB). Source: 12 months ago
View more

Open Data Hub mentions (3)

  • job scheduling for scientific computing on k8s?
    Perhaps have a look at OpenDataHub. While geared for Openshift, see if they solved some of your concerns. Source: 12 months ago
  • Elyra 2.2: R support, updated CLI, and more
    A common approach is to deploy JupyterHub on Kubernetes and configure it for Elyra, like it is done in Open Data Hub on the Red Hat OpenShift Container platform. - Source: dev.to / over 3 years ago
  • Automate your machine learning workflow tasks using Elyra and Apache Airflow
    If you are interested in running pipelines on Apache Airflow on the Red Hat OpenShift Container Platform, take a look at Open Data Hub. Open Data Hub is an open source project (just like Elyra) that should include everything you need to start running machine learning workloads in a Kubernetes environment. - Source: dev.to / over 3 years ago

What are some alternatives?

When comparing CUDA and Open Data Hub, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

C3 AI Suite - The C3 AI Suite uses a model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise-scale AI applications.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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