Python Deep Learning Projects

Defining the model

We will be using a approach from the Keras model that we used earlier in this project to build this model. To build a more complex model, we will use TensorFlow to write each layer from scratch. TensorFlow gives us, as data scientists and deep learning engineers, more fine-tuned control over our model's architecture. 

For this model, we will use the code in the following block to create two placeholders that will store the input and output values:

import tensorflow as tfimport picklefrom tensorflow.contrib import rnn    def build(self, input_number, sequence_length, layers_number, units_number, output_number):        self.x = tf.placeholder("float", [None, sequence_length, input_number]) self.y = tf.placeholder("float", [None, output_number]) ...