Tutorials & Examples
Python Jupyter Notebook (Recommended)
Assuming you have completed Getting Started, use the CNTK Python Jupyter notebook tutorials to gain familiarity with the toolkit. You may want to start with the CNTK 100 series tutorials before trying out higher series that cover a range of different applications including image classification, language understanding, reinforcement learning and others.
Additional Python recipes:
- 'Build your own image classifier using Transfer Learning' provides two examples for custom image classifiers using transfer learning.
- 'Object detection using Fast R-CNN' describes how to train Fast R-CNN on PASCAL VOC data and custom data for object detection.
- 'Object-Detection-using-Faster-R-CNN' describes how to train Faster R-CNN on PASCAL VOC data and custom data for object detection.
You can also try out the tutorials live with pre-installed CNTK in Azure Notebooks for free.
Refer to Examples to find examples of building networks in CNTK using the supported APIs.