- Keras Tutorial
- Keras - Home
- Keras - Introduction
- Keras - Installation
- Keras - Backend Configuration
- Keras - Overview of Deep learning
- Keras - Deep learning
- Keras - Modules
- Keras - Layers
- Keras - Customized Layer
- Keras - Models
- Keras - Model Compilation
- Keras - Model Evaluation and Prediction
- Keras - Convolution Neural Network
- Keras - Regression Prediction using MPL
- Keras - Time Series Prediction using LSTM RNN
- Keras - Applications
- Keras - Real Time Prediction using ResNet Model
- Keras - Pre-Trained Models
- Keras Useful Resources
- Keras - Quick Guide
- Keras - Useful Resources
- Keras - Discussion
Keras - Pooling Layer
It is used to perform max pooling operations on temporal data. The signature of the MaxPooling1D function and its arguments with default value is as follows −
keras.layers.MaxPooling1D ( pool_size = 2, strides = None, padding = 'valid', data_format = 'channels_last' )
Here,
pool_size refers the max pooling windows.
strides refer the factors for downscale.
Similarly, MaxPooling2D and MaxPooling3D are used for Max pooling operations for spatial data.
Advertisements