Frequently Asked Questions

What do I have to do to integrate you and begin seeing the insights in your system?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
I want to use your system! What do you need from me / What do I need to do?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
Which types of issues does your system detect?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
Which types of issues does your system detect?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
Why shouldn’t I just use the monitoring that already exists in the cloud platforms?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
Which types of models do you support?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
I have a complex pipeline, which consists of an ensemble and different types of rules which originate in business logic. Does your system support this?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
My ML pipeline runs in multiple locations across the organization’s infrastructure. The raw data, pre-processing python code, and model inference are all in different places. Where should I place Deepchecks in order to get valuable insights?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
When I consider deploying a new version of my model into production, I typically run an A/B test with the current version. Can Deepchecks help me with this phase, or is the system only suited for monitoring one deployed version?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
I have sensitive data that I wouldn’t like to expose. How does Deepchecks deal with this?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
I already feel like I have too many dashboards. Can’t you just send me your metrics and the alerts so I can read them using a generic monitoring system?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.
I have large volumes of data being streamed to my ML model. Can Deepchecks handle this?
We support any models adhering to the scikit-learn model api. This includes: TensorFlow, CatBoost, LightGBM, Keras, XGBoost, Caffe and scikit-learn models (as well as many others).
In addition we also support multi phase models, ensembles and models combined with business logic.

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