Updated separate video links to single YouTube version with time indexes
@@ -127,13 +127,13 @@ Finally, add the output layer:
- DLPy API documentation [sassoftware.github.io/python-dlpy](https://sassoftware.github.io/python-dlpy/).
- [SAS SWAT for Python](http://github.com/sassoftware/python-swat/)
- [SAS ESPPy](https://github.com/sassoftware/python-esppy)
-- A series of Videos on DLPy examples:
- * [Introduction to the series](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001746946001)
- * [Image classification using CNNs](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001747449001)
- * [Object detection using TinyYOLOv2](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001747750001)
- * [Import and export deep learning models with ONNX](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001743770001)
- * [Text classification and text generation using RNNs](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001746471001)
- * [Time series forecasting using RNNs](http://players.brightcove.net/1872491364001/default_default/index.html?videoId=6001747359001)
+- Watch: Introduction to DLPy and examples (YouTube):
+ * [Introduction Deep Learning with Python (DLPy) and SAS Viya](https://www.youtube.com/watch?v=RJ0gbsB7d_8)
+ * [Image classification using CNNs](https://www.youtube.com/watch?v=RJ0gbsB7d_8&start=125)
+ * [Object detection using TinyYOLOv2](https://www.youtube.com/watch?v=RJ0gbsB7d_8&start=390)
+ * [Import and export deep learning models with ONNX](https://www.youtube.com/watch?v=RJ0gbsB7d_8&start=627)
+ * [Text classification and text generation using RNNs](https://www.youtube.com/watch?v=RJ0gbsB7d_8&start=943)
+ * [Time series forecasting using RNNs](https://www.youtube.com/watch?v=RJ0gbsB7d_8&start=1185)
- [SAS Deep Learning with Python made easy using DLPy](https://blogs.sas.com/content/subconsciousmusings/2019/03/13/sas-deep-learning-with-python-made-easy-using-dlpy/)
### Contributing
