Neurovation.net
Neurovation.net is a no-code platform for building machine learning models and applications without coding. It provides a visual interface to train models, deploy them, and monitor their performance.
nocode
visual-interface
machine-learning-models
monitoring
Neurovation: No-Code Machine Learning Platform | Neurovation
Neurovation.net is a no-code platform for building machine learning models and applications without coding. It provides a visual interface to train models, deploy them, and monitor their performance.
What is Neurovation.net?
Neurovation.net is a no-code artificial intelligence platform that allows anyone to build, train and deploy machine learning models and applications without writing any code. It provides an intuitive visual interface and drag-and-drop components to assemble machine learning workflows.
Some key capabilities of Neurovation.net include:
- Visual model builder to train models like classifiers, regressors, forecasters, recommenders etc using various techniques like neural networks, random forests etc.
- Pre-built modules for text, image, audio and time-series data processing.
- MLOps tools to deploy models via APIs, schedule training jobs, monitor performance etc.
- Visual app builder to create web apps powered by the ML models and share them.
- Secure data storage and version control for models and apps.
- Collaboration features to work together with team members.
Overall, Neurovation.net aims to make machine learning and model building quick and accessible to domain experts, citizen data scientists and ML teams - without needing any coding.
Neurovation.net Features
Features
- Visual interface for building ML models without coding
- Pre-built templates for common ML tasks like classification and regression
- Drag-and-drop interface for assembling ML pipelines
- Model monitoring and performance analytics tools
- Deployment options for putting models into production
- Collaboration features for teams to work together
Pricing
- Freemium
- Subscription-Based
Pros
Lowers barrier to entry for non-coders
Speeds up development process compared to coding ML from scratch
Visual interface is intuitive and easy to learn
Integrated end-to-end platform for full ML workflow
Collaboration features help teams work efficiently
Cons
Less flexibility than coding custom ML solutions
Limited to built-in model types, datasets and algorithms
Advanced users may prefer more control with code
Hosted platform raises potential data privacy concerns
Official Links
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