The best alternatives to Deepchecks: Continuous Validation for AI are Signals Network, Pythagora, and CLIP Playground. If these 3 options don't work for you, we've listed over 10 alternatives below.
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The new version of Signals is live! No download, no installation, Signals is a browser-based algorithmic trading laboratory for creating, analyzing, and executing trading models on high-resolution financial data with the computational power of our data center.
CLIP Playground lets you test OpenAI's new model CLIP from your browser. CLIP is a GPT-3 like AI you can use to perform a variety of tasks that pair both images and text.
Need feedback on your new tool or feature? 🧐 Get ready to see your ideas meet real-world evaluators. ✨ Modeled on our favourite "Product Hunt", MVPeeps focuses on connecting 'MakerPeeps' with 'TesterPeeps', before the creations hit the market. 🎯
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.
Heatseeker removes the guesswork from your product decisions through real-time testing and learning in the market, powered by AI. We help your business in reaching more users quickly, synthesizing data from these experiments & turning you into a lean startup.
Pandera is the open source framework for data testing, built for data scientists and ML engineers. It provides a simple, zero-configuration Python library to help you write complex schemas with ease and validate critical points of your pipeline in production.
One-of-a-kind data modeling tool that lets you design a blueprint of your application data. You can then generate the model code for your app's entire technology stack.
A powerful tool that gives you an in-depth analysis on the most important tags and the content of your webpage. Moreover, it can Improve the performance of your webpage's with key metrics and suggestions. Available at different monthly subscription plans or one-time payment for lifetime usage.
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.
QBox analyzes and benchmarks your chatbot training data by visualizing and understanding where it does and doesn’t perform, and why (for your NLP). With this insight, you can make informed decisions about how you develop the performance of your chatbot.
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