Visually explore, understand, and present your data.
Обновлено 2024-09-12 01:00:31 +03:00
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
machine-learning
data-science
jupyter
ml
ui
explainable-ai
explainable-ml
fairness
fairness-ai
fairness-ml
interpretability
machinelearning
responsible-ai
visualization
widget
widgets
data-analysis
data-visualization
error-analysis
explainability
Обновлено 2024-08-07 04:34:48 +03:00
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
machine-learning
data-science
ml
visualization
jupyter
data-visualization
ui
machinelearning
widgets
data-analysis
explainable-ai
explainable-ml
fairness-ai
fairness-ml
interpretability
fairness
responsible-ai
explainability
widget
error-analysis
Обновлено 2024-08-07 04:34:48 +03:00
A web app to create and browse text visualizations for automated customer listening.
Обновлено 2023-10-27 06:29:49 +03:00
The AAS WorldWide Telescope user manual
Обновлено 2023-08-04 00:16:55 +03:00
An expressive visual storytelling environment for presenting timelines on the web and in Power BI. Developed at Microsoft Research.
Обновлено 2023-04-17 23:43:08 +03:00
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Обновлено 2022-09-23 02:59:07 +03:00
Sample Vega-Lite Wrapper as a PowerBi Custom Visual
Обновлено 2022-02-18 00:04:15 +03:00
Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.
azure
data
r
visualization
workshop-materials
anomaly-detection
azure-databricks
databricks-notebooks
timeseries-forecasting
time-series-analysis
sparksql
311-data
aiforsocialgood
anomalydiscovery
datascience-machinelearning
eda
geospatial
leaflet
opendata
sparkr
Обновлено 2021-05-03 23:14:01 +03:00
A tool for analyzing and visualizing discrete temporal events
Обновлено 2018-08-15 11:24:51 +03:00