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    3. Alternatives
    The best alternatives to NannyML are TensorFlow, Intersect Labs, and Openlayer. If these 3 options don't work for you, we've listed over 10 alternatives below.
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    Best alternatives to NannyML
    • TensorFlow is a fast, flexible, and scalable open-source machine learning library for research and production.
    • Intersect Labs puts the world's most advanced algorithms in your hands with just three clicks. Make machine learning an easy, straightforward part of your workflow.
    • Openlayer is a powerful testing and observability platform for ML. It lets you collaborate with others on finding issues in models and data, debugging them, and committing new versions.
    • This question does not exist. This is what happens when you train a language model on a data dump of Stack Overflow. Click "Fresh Question" to load a new one. Share the permalink if you find an interesting one!
    • From the makers of Lucidchart and Lucidspark, Lucidscale is the cloud visualization solution that helps organizations see, understand and optimize cloud environments, enabling technical and non-technical users to achieve better understanding and alignment.
    • Monitor ML tracks the performance of models throughout their lifecycle and connects them to business metrics. We support model tracking, metric logging/analysis/alerting and production event logging. You choose the framework, we monitor the model.
    • Aqueduct automates the engineering required to take data science to production. By abstracting away low-level cloud infrastructure, Aqueduct enables data teams to run models anywhere, publish predictions where they're needed, and monitor results reliably.
    • Today’s data stack was built for yesterday’s software engineers. Data scientists deserve their own tools. Magniv is an open-source Python library that lets data scientists deploy apps independently, without relying on support from software engineers.
    • Build and deploy ML models with ease using Semiring. Start with 5 data samples to craft datasets, fine-tune with our models, and deploy via a simple API. No ML know-how is needed.
    • Grab a CSV, upload it, and start exploring your data. Make graphs and analyze data without writing code.
    • No more coding needed, just add one line to your R script in which you call our magic shinify() function. Shinify automatically creates a shiny server and visual interface for you to interact with your machine learning or statistical model.
    • Qualdo™ helps enterprises monitor mission-critical ML & data issues, errors, and quality using Advanced Data & ML Engineering.
    • Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services.