Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
Обновлено 2024-02-08 18:29:01 +03:00
With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
microsoft
machine-learning
data-science
anomaly-detection
nlp-machine-learning
sampling-strategies
text-analysis
text-classification
text-summarization
azure-automl
cleansing-data
datavisualization
responsible-ml
Обновлено 2023-08-03 09:43:02 +03:00
This is a repo to implement Anomaly Detection which is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations.
Обновлено 2023-01-25 22:08:32 +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
Deploying a Batch Scoring Pipeline for Python Models
Обновлено 2020-01-28 22:21:04 +03:00