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About

IREN’s AI Cloud is a GPU-cloud platform built on NVIDIA reference architecture and non-blocking 3.2 TB/s InfiniBand networking, offering bare-metal GPU clusters designed for high-performance AI training and inference workloads. The service supports a range of NVIDIA GPU models with specifications such as large amounts of RAM, vCPUs, and NVMe storage. The cloud is fully integrated and vertically controlled by IREN, giving clients operational flexibility, reliability, and 24/7 in-house support. Users can monitor performance metrics, optimize GPU spend, and maintain secure, isolated environments with private networking and tenant separation. It allows deployment of users’ own data, models, frameworks (TensorFlow, PyTorch, JAX), and container technologies (Docker, Apptainer) with root access and no restrictions. It is optimized to scale for demanding applications, including fine-tuning large language models.

About

Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI and ML engineers, researchers, and enterprises wanting a tool to train, fine-tune, and deploy sophisticated models

Audience

Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5

Pros & Cons from Real Users

Pros

  • I mostly code in Python, so using Keras for my deep learning needs wasn't too hard to get used to, given the abundance of documentation and ease of writing modular code with its API.

Cons

  • Keras only has high level APIs, unlike Tensorflow, which has both high and low level support.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

IREN
Australia
www.iren.com/solutions/gpu-cloud/ai-cloud

Company Information

Keras
United States
keras.io

Alternatives

Alternatives

Categories

Categories

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Integrations

JAX
TensorFlow
Akira AI
BentoML
Cleanlab
Comet
Dataiku
DeepSeek
Gradient
Graphcore
Guild AI
Llama
ModelOp
Radicalbit
Spell
Superwise
Thunder Compute
WEKA

Integrations

JAX
TensorFlow
Akira AI
BentoML
Cleanlab
Comet
Dataiku
DeepSeek
Gradient
Graphcore
Guild AI
Llama
ModelOp
Radicalbit
Spell
Superwise
Thunder Compute
WEKA
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