Deepchecks
For Model & Data Testing

Iteratively run test suites on your data and models. Run tests within a notebook / IDE or as part of your
CI/CD.

Thoroughly Test Your Data and
Models from Research to Production

Adopt Best Practices

Adopt Best Practices

While most software teams have clear
methodologies around testing & QA, for most
teams of ML Practitioners.

Are you using ML testing best practices? Do you
have standardized processes?

Standardize Research Reviews

Standardize Research
Reviews

Some teams don’t really do ML testing at all,
other teams have well-defined research review
processes, which usually involve tedious
processes which your top researchers do not
have the time for!

Set Up Processes That Enable You to Scale

Set Up Processes That
Enable You to Scale

In order to speed up model development and
maintenance, you will need to have rigorous
testing. Usually, that requires a lot of coding. The
best way to enable scale is to use a testing
framework, covering all models with minimal
coding efforts.

You Already Know You Should Start

You Already Know You
Should Start

Yes, you already know we’re right about this. You
just never had a simple solution at your fingertips.
Well, now you do. And it's free!

Increase Velocity With Ease by
Integrating ML Testing into CI/CD

Test Each New Version, Not Just the First One

Test Each New Version, Not
Just the First One

Before deploying your machine learning model to
production for the first time, you probably
explored it inside and out. What about the next
model versions, that have only minor differences
from the original model?

Set Up Processes That Enable You to Scale

Set Up Processes That
Enable You to Scale

Will your top team members spend their precious
time thoroughly validating each new version? Will
that continue to happen as you have more
models and more variants for each model?

Adopt Best Practices from Software Engineering

Adopt Best Practices from
Software Engineering

Here’s an alternative: Build well-defined tests
that run on your model and data, each time there
is a new version. Just like CI/CD is done in “classic
software”!

Easy to Install

Using Deepchecks is simple: For example, setting
up Deepchecks Open Source for tabular data
requires only two lines of code.

Please refer below for more information:

pip install  -U deepchecks from  deepchecks.tabular.suites import  train_test_validation

Run Test Suites for CI/CD

Deepchecks Open Source can be used for CI/CD
by integrating just a few lines of code to your CI/
CD scripts. This will help you to ensure that your
re-trained model will not cause issues when
deployed to production.
Book a Demo
on: push: ['main'] job: run_suites:     train_dataset: 'load.py:get_train_dataset'
    test_dataset: 'load.py:get_test_dataset'
    model: 'load.py:get_model'
    suites: ['custom_suites.py:my_model_evaluation_suite']

Open Source & Community

Deepchecks is committed to keeping the ML evaluation package open-source and community-focused.

Recent Blog Posts

Precision vs. Recall in the Quest for Model Mastery
Precision vs. Recall in the Quest for Model Mastery