loss-landscape VS deepchecks

Compare loss-landscape vs deepchecks and see what are their differences.

loss-landscape

Code for visualizing the loss landscape of neural nets (by tomgoldstein)

deepchecks

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. (by deepchecks)
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loss-landscape deepchecks
2 15
2,642 3,350
- 3.2%
0.0 8.2
about 2 years ago 11 days ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

loss-landscape

Posts with mentions or reviews of loss-landscape. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

deepchecks

Posts with mentions or reviews of deepchecks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-18.

What are some alternatives?

When comparing loss-landscape and deepchecks you can also consider the following projects:

TorchDrift - Drift Detection for your PyTorch Models

great_expectations - Always know what to expect from your data.

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

model-validation-toolkit - Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.

backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

feast - Feature Store for Machine Learning

cockpit - Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

postgresml - The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

giskard - 🐢 Open-Source Evaluation & Testing framework for LLMs and ML models