  Human does their daily activity and cooking by teaching and imitating with
the help of their vision and understanding of the difference between materials.
Teaching a robot to do coking and daily work is difficult because of variation
in environment, handling objects at different states etc. Pouring is a simple
human daily life activity. In this paper, an approach to get pouring sequences
were analyzed for determining the velocity of pouring and weight of the
container. Then recurrent neural network (RNN) was used to build a neural
network to learn that complex sequence and predict for unseen pouring
sequences. Dynamic time warping (DTW) was used to evaluate the prediction
performance of the trained model.
