JittorVis - Visual understanding of deep learning models
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Updated
Apr 18, 2022 - Python
JittorVis - Visual understanding of deep learning models
🌟 An end-to-end full-stack data science project, including modelling, MLOps, and data storytelling. ✨
Spatio-Temporal Tag and Photo Location Clustering for generating Tag Maps
[PacificVis 2025] Multi-Criteria Exploratory Dashboard
A visual analytics environment for supervised text classification and model evaluation.
FeatureEnVi: Visual Analytics for Feature Engineering Using Stepwise Selection and Semi-Automatic Extraction Approaches
Visual analysis approach presented in the papers "Visualization-based improvement of neural machine translation" (Computers & Graphics, 2021) and "Visual-Interactive Neural Machine Translation" (Graphics Interface, 2021).
Visual analysis approach presented in the paper "Exploring visual quality of multidimensional time series projections", published by the journal Visual Informatics.
StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
Tracking Daily COVID-19 Infection Count in European Countries using Hadoop MapReduce and Python
Visualizations and predictive models of traffic stop data from Charlotte, NC
VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization
Instance of Tiramisù framework designed to provide insights about personal work processes
Iris Dataset Analysis Using Dash
A visual debugging tool for fine-tuned BERT models for (multilabel) sequence classification tasks
Source code for the paper "Unsupervised Video Summarization via Multi-source Features" published at ICMR 2021
Visual analytics app for exploring machine learning classifications.
This repo contains code for conducting image classification on a dataset of fruit images. Two models are fit to the data; a simple sequential model which is akin to multiclass logistic regression, and a large pretrained CNN model (VGG16).
Under development novel visualization method using Parallel Coordinates in multi-row layouts for visual analytics and visual computing of image data in the natural ground-truth pixel order.
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