TensorFlow 2.0 is coming really soon. Therefore, we quickly show some useful features, i.e., save and load a pre-trained model, with v.2 syntax. To make it more intuitive, we will also visualise the graph of the neural network model. Benefits of saving a model Quick answer: to save time, easy-share, and fast deploy. A SavedModel contains a complete TensorFlow program, including weights and...

## A.I in agriculture – Fruit Grading with Keras (part 2)

In part 1, we introduced fruit classification with pure python implementation. In this part, we will use the Keras library instead. What is Keras Keras is an open-sourceneural-network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. Designed to enable fast experimentation...

## A gentle demonstrate to Tensorflow’s graph and session

When starting Tensorflow (TF), many may find that the result cannot be obtained immediately. Rather, you must use a session or interactive session. TensorFlow uses a dataflow graph to represent your computation in terms of the dependencies between individual operations. This leads to a low-level programming model in which you first define the dataflow graph, then create a...

## Convolutional Neural Network with CIFAR and Tensorflow (example)

Fig 1: A CNN sequence to classify handwritten digits (src: medium) In this article, we assume that you already understand the basic concepts of a convolutional neural network (CNN), e.g. one-hot coding, convolution, pooling, fully-connected layer, activation functions. If you are totally new to these terms, please find and read our other articles. The problem We will use Tensorflow to build a...