A python library to send data to Arize AI!
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Updated
May 22, 2024 - Python
A python library to send data to Arize AI!
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
Sample notebooks that use the Openlayer Python API
Predict which powerlifters will have the highest one-rep-max deadlift
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.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
Java client to interact with Arize API
A proof-of-concept for the implementation of an early fault detection system in oil wells, designed to enhance operational efficiency and reduce costs.
Developed an efficient system to empower retailers with profitable insights & maintain a competitive edge in the dynamic retail industry.
Writeup on classification model for predicting outcomes of NFL games, focusing on explainability. (+ project writeup)
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.
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
This project implements an ML regression model for predicting cancer death rate in US.
Capture fundamentals around ethics of AI, responsible AI from principle, process, standards, guidelines, ecosystem, regulation/risk standpoint.
CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)
Example projects for Arthur Model Monitoring Platform
This project develops an ML binary classification model to predict phishing webpages.
Explaining Trees (LightGBM) with FastTreeShap (Shapley) and What if tool
Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
Machine Learning Final Project - December 04, 2021
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