logheatgarden•This week
I built an instant no-code AI tool for training & explaining regression/classification models
Hey everyone!
I recently developed a no-code SaaS tool aimed at simplifying and speeding up machine learning workflows, particularly for regression and classification tasks. I’d love to get feedback from the community here, especially from those who are experienced with machine learning and data science workflows. I’ll give a quick rundown of the tool's features, but I want to emphasize that I’m here more to learn about what would be valuable for you than to promote anything.
The basic idea: This tool allows you to go from a raw dataset (CSV or tabular text format) to a trained ML model in minutes, rather than needing weeks or months of coding, hyperparameter tuning, and visualization work. It's designed to be intuitive for users without a strong coding background but still offers the depth that experienced users would need.
Here’s how it works:
Data Upload & Prep:
Start by uploading a CSV or other tabular format dataset. The tool includes data prep steps that are designed to be simple but cover essentials (e.g., missing value handling, scaling).
Model Training & Tuning: You can choose between regression and classification models, with automatic hyperparameter tuning happening in the background (under a time limit that you can set). It aims to find a good balance without needing direct input but does allow for manual adjustments if desired.
Performance Analysis: It provides aggregated performance metrics like F1, recall, precision, R2, and others, alongside charts like AUROC, confusion matrices, and feature importance charts. I also included SHAP plots for deeper insight into feature contributions, as I know they’re becoming a standard for interpretability.
Inference Options: The tool lets you do inference on either manually entered data or batch data (again, via CSV). The UI is lightweight and tries to make this as seamless as possible.
What I’m hoping to get feedback on:
Are there core features that feel like they’re missing?
My goal was to provide a well-rounded suite for non-technical users but with enough depth for data scientists to find value.
Does this kind of tool fit into your workflow?
Or would something like this be more of a beginner tool?
How valuable is explainability?
I know SHAP is popular, but I’m curious if it actually makes it into the workflows of many data scientists here.
Anything else you’d like to see in a tool like this?
I know that there are a lot of no-code ML tools out there, so I’m not trying to reinvent the wheel—I just tried to make something a bit more straightforward while still incorporating some flexibility and depth. If you’ve used similar tools or have thoughts on what would make something like this actually useful in practice, I’d really appreciate any insights!
Thank you so much for reading, and looking forward to any feedback you’re willing to share.
Beta testers are welcome, currently forming a list.
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