This document discusses using artificial intelligence and deep learning techniques for yoga pose estimation and classification. Specifically, it proposes training a model using the PoseNet and OpenPose frameworks on a dataset of yoga pose videos to identify key points in the human body and classify the pose. The model would use convolutional neural networks and long short-term memory to process video frames in real-time and provide classification scores for the accuracy of pose identification. This type of system could help improve health and provide feedback to users on yoga pose form without an instructor. However, it is currently limited to a small number of poses and requires internet and webcam access.