Panadda KongsilpCNN: Tom & Jerry… Can you catch me?The previous chapter we talk about “how to build the CNN model” for image classification by classifying which is a dog and cat. In this…Aug 5, 2019Aug 5, 2019
Panadda KongsilpCNN: Step 4 — ConnectionIn this step, we’re adding a whole artificial neural network to our convolutional neural network.Jul 22, 2019Jul 22, 2019
Panadda KongsilpCNN: Step 2 — FlatteningToday, we’re talking about flattening.Jul 22, 2019Jul 22, 2019
Panadda KongsilpCNN: Step 2 - Max Poolingwhat is pooling and why do we need it?Jul 22, 2019Jul 22, 2019
Panadda KongsilpCNN: Step 1 — ConvolutionIf we have input image like this, then we have a three-by-three feature detector.Jul 22, 2019Jul 22, 2019
Panadda KongsilpWhat is Convolution Neural Network?If you have an input image, pass it through the convolution neural network, you will have an output label. Convolution neural network will…Jul 22, 2019Jul 22, 2019
Panadda KongsilpSomething about Convolution Neural Network (CNN)In order to understand the convolution neural network, we need to go discuss on these following topics;Jul 22, 20191Jul 22, 20191
Panadda KongsilpBuilding an ANNLet’s build ANN model. This article uses the dataset of a bank customer, we need to predict who will be left or who will stay.Jul 22, 2019Jul 22, 2019
Panadda KongsilpGradient DescentAs we said that our goal is to minimize the cost function. From the previous chapter, our neural network is very simple. So you need to…Jul 21, 2019Jul 21, 2019
