Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
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Updated
Aug 30, 2023 - Jupyter Notebook
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
A python library to send data to Arize AI!
Sample notebooks that use the Openlayer Python API
code for studying OpenAI's CLIP explainability
CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)
Java client to interact with Arize API
Capture fundamentals around ethics of AI, responsible AI from principle, process, standards, guidelines, ecosystem, regulation/risk standpoint.
Example projects for Arthur Model Monitoring Platform
Explaining Trees (LightGBM) with FastTreeShap (Shapley) and What if tool
A proof-of-concept for the implementation of an early fault detection system in oil wells, designed to enhance operational efficiency and reduce costs.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
Machine Learning Individual Project - November 23, 2021
Developed an efficient system to empower retailers with profitable insights & maintain a competitive edge in the dynamic retail industry.
Study on the performance of pre-trained models (VGG16, EfficientNetb0, ResNet50, ViT16) with weight fine tuning, as well as classical ML algorithms (Naive Bayes, Logistic Regression, Random Forest) on a dataset of 6.806 fungi microscopy Images utilizing Pytorch.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
This project develops an ML binary classification model to predict phishing webpages.
Machine Learning Final Project - December 04, 2021
Writeup on classification model for predicting outcomes of NFL games, focusing on explainability. (+ project writeup)
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