A simple deep learning model for stock price prediction using TensorFlow

In the figure above, two numbers are supposed to be added. Those numbers are stored in two variables, a and b. The two values are flowing through the graph and arrive at the square node, where they are being added. The result of the addition is stored into another variable, c. Actually, a, b and c can be considered as placeholders. Any numbers that are fed into a and b get added and are stored into c. This is exactly how TensorFlow works. The user defines an abstract representation of the model (neural network) through placeholders and variables. Afterwards, the placeholders get "filled" with real data and the actual computations take place.