Wrapper exposing PyTorch models through the scikit-learn estimator API, so grid search, pipelines and callbacks work directly with neural networks. Built and maintained by WIEWAVE for Azure Marketplace and AWS Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace and AWS Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Published |
| Google Cloud Marketplace | Available on request |
Need it on another marketplace, or as a private offer for your organisation? cloud@wiewave.com
Each image follows its distribution's own provisioning model, package manager and security tooling — not one build relabelled several times.
LTS and interim releases, Minimal and Pro variants, built to Canonical's cloud-image conventions.
Stable and oldstable, with backports where a workload needs a newer runtime than the release ships.
The same four steps behind every offer we've published, including the hardening and CIS Benchmark checks every build goes through.
The distribution, licensing model and target marketplaces are agreed before anything is built.
Packer templates, Ansible provisioning and a pinned package set — then hardened, scanned and checked against the CIS Benchmark for its distribution.
Taken through each cloud's own certification pipeline before it goes live on the marketplace.
Rebuilt on the upstream security cadence and re-published, with old versions retired without breaking deployments.
If yours isn't here, ask our marketplace team directly.
GPU-ready training and inference images with drivers, CUDA and frameworks already matched to each other.
Data-centric AI platform where labelling functions and weak supervision generate training data programmatically instead of relying on manual annotation.
Industrial natural language processing library for Python offering tokenization, tagging, named entity recognition and pretrained pipelines for dozens of languages.
Reinforcement learning library built on PyTorch implementing PPO, DQN, SAC and A2C behind a consistent training, evaluation and logging API.
Python package for estimating statistical models, running hypothesis tests and exploring data, preinstalled with its NumPy, SciPy and pandas dependencies.
Python framework that turns plain scripts into interactive data and machine-learning web apps, with the runtime and server preconfigured on port 8501.
Neural text-to-speech architecture that generates mel spectrograms from text for a vocoder such as WaveGlow, packaged with PyTorch and CUDA dependencies.
Tell us the distribution, the marketplace and the commercial model — we'll build, certify and publish it as a public listing or a private offer.
