For human action recognition, you will be using skeleton data that encodes the 3D locations of 25 body joints. The data is collected by Kinect v2. There are 10 different action classes. There are 4000 training sequences, 800 validation sequences, and 1000 test sequences. Each sequence has 15 frames, each frame is a 75-dimension vector (the xyz positions of 25 joints). You will first train a LSTM for action classification. 

Then try to improve the network architecture and attach your results with the jupyter notebook. Also add the hyper-parameters explored. 

GLHF!