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Shapash Alternatives
Similar projects and alternatives to shapash
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shap
A game theoretic approach to explain the output of any machine learning model.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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LIME
Discontinued Tutorial notebooks on explainable Machine Learning with LIME (Original work: https://arxiv.org/abs/1602.04938) (by longpollehn)
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GlassCode
This plugin allows you to make JetBrains IDEs to be fully transparent while keeping the code sharp and bright.
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eurybia
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
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CARLA
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms (by carla-recourse)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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.
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evidently
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
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cleverhans
An adversarial example library for constructing attacks, building defenses, and benchmarking both
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yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
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stylegan2-pytorch
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
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explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
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uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
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WeightWatcher
The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
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Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
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shapash reviews and mentions
- [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process?
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This A.I.-generated artwork, Théâtre D'opéra Spatial, won first place at an art competition, and the art community isn't happy about it
There's work being done in that regard (like this python module), but as far as I know it's very clearly statistical guesstimates, and though it "works", the mathematical foundations are still somewhat shaky. There are heuristics in there we can't get rid of for now. But it's still better than nothing. Waaaaaay better than nothing.
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Hacker News top posts: Jun 14, 2022
Shapash – Python library to make machine learning interpretable\ (4 comments)
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State of the Art data drift libraries on Python?
Try out eurybia, from the author of shapash which is a brilliant library as well.
- [D] Has anyone ever used the SHAP and LIME models in machine learning?
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A note from our sponsor - SaaSHub
www.saashub.com | 28 Mar 2024
Stats
MAIF/shapash is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of shapash is Jupyter Notebook.