Building Recurrent Neural Networks Using TensorFlow

Ahmet Taspinar walks us through creating a recurrent neural network topology using TensorFlow:

As we have also seen in the previous blog posts, our Neural Network consists of a tf.Graph() and a tf.Session(). The tf.Graph() contains all of the computational steps required for the Neural Network, and the tf.Session is used to execute these steps.

The computational steps defined in the tf.Graph can be divided into four main parts;

  1. We initialize placeholders which are filled with batches of training data during the run.

  2. We define the RNN model and to calculate the output values (logits)

  3. The logits are used to calculate a loss value, which then

  4. is used in an Optimizer to optimize the weights of the RNN.

As a lazy casual, I’ll probably stick with letting Keras do most of the heavy lifting.

Related Posts

Network Analysis With Python In Power BI

Tori Tompkins shows us how to use the NetworkX package in Power BI: The data I used was created to demonstrate this task in Power BI but there are many real-world network datasets to experiment with provided by Stanford Network Analysis Project. This small dummy dataset represents a co-purchasing network of books. The data I loaded […]

Read More

Installing External Python Modules In SQL Server

David Fowler shows how to import an external Python module into SQL Server Machine Learning Services: But how do we go about installing them into SQL Server?  Now I’m a DBA and not a Python wizz so had to do a little digging to figure it out but to be honest, it’s fairly easy. I […]

Read More

Categories

July 2018
MTWTFSS
« Jun Aug »
 1
2345678
9101112131415
16171819202122
23242526272829
3031