Topic: model-interpretability Goto Github
Some thing interesting about model-interpretability
Some thing interesting about model-interpretability
model-interpretability,To predict the rating of a developer using various data captured during an online test
User: abhinav1004
model-interpretability,MSc dissertation project, written in using LaTeX.
User: alvaro-concha
model-interpretability,A machine learning project developing classification models to predict COVID-19 diagnosis in paediatric patients.
User: amascasadesus
model-interpretability,Implementation of the Grad-CAM algorithm in an easy-to-use class, optimized for transfer learning projects and written using Keras and Tensorflow 2.x
User: andreafortini
model-interpretability,Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.
User: ankit-kumar-saini
model-interpretability,Collection of the assignments for Data Science Engineering Methods on National Stock Exchange Dataset and TMNIST dataset
User: anusha-gali
model-interpretability,This repository includes a general informations and examples about how to make a machine learning model just a few lines of code in Python using PyCaret package.
User: ataozarslan
model-interpretability,Sentiment Analysis using Machine Learning
User: csingh26
model-interpretability,Model interpretability for Explainable Artificial Intelligence
User: dg1223
model-interpretability,An Explainable AI technique introduced in the paper Axiomatic Attribution for Deep Networks
User: diwakar-vsingh
model-interpretability,A python script for basic data cleaning/manipulation and modelling based on the open source House Sales Advanced Regression Techniques(Kaggle)
User: dtheod
model-interpretability,squid repository for manuscript analysis
User: evanseitz
model-interpretability,surrogate quantitative interpretability for deepnets
User: evanseitz
model-interpretability,Interpretability and Fairness in Machine Learning
User: fpretto
model-interpretability,A set of tools for leveraging pre-trained embeddings, active learning and model explainability for effecient document classification
User: hellisotherpeople
Home Page: https://huggingface.co/spaces/Hellisotherpeople/Interpretable_Text_Classification_And_Clustering
model-interpretability,Scripts and trained models from our paper: M. Ntrougkas, N. Gkalelis, V. Mezaris, "T-TAME: Trainable Attention Mechanism for Explaining Convolutional Networks and Vision Transformers", IEEE Access, 2024. DOI:10.1109/ACCESS.2024.3405788.
Organization: idt-iti
model-interpretability,Will They Pay? A machine learning solution to understand mobile app user payment behavior
User: jaysmitjadhav
model-interpretability,This repository contains the work in the AI engineer Cognizant virtual training and internship program from forage
User: jayveersinh-raj
model-interpretability,Course project for 6.869: automatic summarization for neural net interpretability
User: jmftrindade
model-interpretability,Tools for easing the handoff between AI/ML and App/SRE teams.
Organization: jozu-ai
Home Page: https://KitOps.ml
model-interpretability,AI to Predict Yield in Aeroponics
User: juliotorrest
model-interpretability,Standardized Serverless ML Inference Platform on Kubernetes
Organization: kserve
Home Page: https://kserve.github.io/website/
model-interpretability,This repository provides R scripts for reproducing virtual species generating, modeling species distribution and final figures related with published manuscript.
User: lukasgabor
model-interpretability,Exercise on interpretability with integrated gradients.
Organization: machine-learning-foundations
model-interpretability,Investigating a neural network response to input parameters using sensitivity analysis techniques.
User: mansooralodhi
model-interpretability,Covid Detection via CT Scan Image Analysis
User: mbdelaresma
model-interpretability,Football Positions: A Multi-class Classification Problem
User: mbdelaresma
model-interpretability,Identifying Hate Speech in Philippie Election-Related Tweets
User: mbdelaresma
model-interpretability,Using LIME and SHAP for model interpretability of Machine Learning Black-box models.
User: mohitr7
model-interpretability,Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
Organization: nyuvis
model-interpretability,Official repository for the paper "Instance-wise Causal Feature Selection for Model Interpretation" (CVPRW 2021)
User: pranoy-panda
model-interpretability,Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
User: rehmanzafar
model-interpretability,erformed a predictive analysis on the customer's Bank Loan Application data to predict loan status. Using python, pandas, scipy, seaborn, AutoML libraries, and machine learning techniques. Used Machine Learning techniques to accurately predict the evaluation scheme if the particular loan will be 'Fully Paid' or 'Charged Off'. This means if Bank accepts a particular person's loan application will it be 'Fully Paid' or 'Charged Off'
User: sanketsanap5
model-interpretability, A major gas and electricity utility that supplies to SME. The power-liberalization of the energy market in Europe has led to significant customer churn.Building a churn model to understand whether price sensitivity is the largest driver of churn.Verifying the hypothesis of price sensitivity being to some extent correlated with churn.
User: shaktipanda1235
model-interpretability,CNN Visualization using PyTorch
User: sharathhebbar
model-interpretability,Softmax-as-intermediate-layer-CNN
User: sharathhebbar
model-interpretability,Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.
User: shuyib
model-interpretability,Visualizing an XGBoost model in R using a sunburst plot (using inTrees)
User: sidjain1412
model-interpretability,The project provides explanation of what SHAP is and how it can be used to interpret model. Also contains Notebook with detail on model interpretability method SHAP and code implementation on Heart disease dataset.
User: srushti104
model-interpretability,Overview of different model interpretability libraries.
User: tannergilbert
Home Page: https://gilberttanner.com/tag/model-interpretation/
model-interpretability,Class Activation Map (CAM) Visualizations in PyTorch.
User: tramac
model-interpretability,The "keras-translator" helps you to understand a keras trained model.
User: vafaei-ar
model-interpretability,pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...
User: yizt
model-interpretability,Pytorch Implementation of recent visual attribution methods for model interpretability
User: yulongwang12
model-interpretability,Code for "Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability" (https://arxiv.org/abs/2010.09750)
User: zphang
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