updated model card

README.md

@@ -6,24 +6,18 @@ tags:
 - anomaly-detection
 ---
 
-## Model description
-
-Timeseries anomaly detection using an Autoencoder
+## Timeseries anomaly detection using an Autoencoder
 
 This repo contains the model and the notebook to this [Keras example on Timeseries anomaly detection using an Autoencoder.](https://keras.io/examples/timeseries/timeseries_anomaly_detection/)
 
 Full credits to: [Pavithra Vijay](https://github.com/pavithrasv)
 
 
-## Intended uses & limitations
-
-More information needed
+## Background and Datasets
 
-## Training and evaluation data
+This script demonstrates how you can use a reconstruction convolutional autoencoder model to detect anomalies in timeseries data. We will use the [Numenta Anomaly Benchmark(NAB)](https://www.kaggle.com/datasets/boltzmannbrain/nab) dataset. It provides artifical timeseries data containing labeled anomalous periods of behavior. Data are ordered, timestamped, single-valued metrics.
 
-More information needed
 
-## Training procedure
 
 ### Training hyperparameters