Software Alternatives & Reviews

CUDA VS Azure Machine Learning Service

Compare CUDA VS Azure Machine Learning Service and see what are their differences

CUDA logo CUDA

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

Azure Machine Learning Service logo Azure Machine Learning Service

Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.
  • CUDA Landing page
    Landing page //
    2023-05-23
  • Azure Machine Learning Service Landing page
    Landing page //
    2023-07-22

CUDA videos

1971 Plymouth Cuda 440: Regular Car Reviews

More videos:

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

Azure Machine Learning Service videos

What is Azure Machine Learning service and how data scientists use it

More videos:

  • Review - Azure Machine Learning service: Part 2 Training a Model

Category Popularity

0-100% (relative to CUDA and Azure Machine Learning Service)
Data Science And Machine Learning
AI
24 24%
76% 76
Data Science Tools
0 0%
100% 100
Machine Learning Tools
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare CUDA and Azure Machine Learning Service

CUDA Reviews

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Azure Machine Learning Service Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: The Azure Machine Learning service lets developers and data scientists build, train, and deploy machine learning models. The product features productivity for all skill levels via a code-first and drag-and-drop designer, and automated machine learning. It also features expansive MLops capabilities that integrate with existing DevOps processes. The service touts...

Social recommendations and mentions

Based on our record, CUDA should be more popular than Azure Machine Learning Service. It has been mentiond 36 times since March 2021. 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: 11 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

Azure Machine Learning Service mentions (4)

  • AI Team Collaboration with Azure ML Studio
    Building an AI solution requires more than just one person. You need a team of experts who can work together efficiently and creatively. That’s why you need a platform that supports collaboration and communication among your AI team members. Azure Machine Learning Studio is not only a powerful infrastructure for computation and technical tasks, but also a management tool that helps you organize and streamline your... - Source: dev.to / 10 months ago
  • Databricks 2022 vs Databricks 2025
    I'm biased, but giving my honest personal opinion here, I think this sounds like a bad idea. I'm not optimistic about Databricks long term. They are a data prep company masquerading as a data science company. Nothing wrong with that, but Spark resources are expensive compared with SQL, and they are at risk from all fronts (Cloud providers, Snowflake, AI/ML platform players, etc.). I see their Databricks controlled... Source: about 2 years ago
  • 20+ Free Tools & Resources for Machine Learning
    Azure Machine Learning An enterprise-grade service for the end-to-end machine learning life cycle that allows you to build models at scale. - Source: dev.to / about 2 years ago
  • Jobs which combine Chemical Engineering and Computer Science
    Azure Machine Learning (specifically for Energy and Manufacturing. Source: about 3 years ago

What are some alternatives?

When comparing CUDA and Azure Machine Learning Service, 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.

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

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

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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

NumPy - NumPy is the fundamental package for scientific computing with Python