Keras Locally-connected Layers LocallyConnected1D keras.layers.LocallyConnected1D(filters, kernel_size, strides=1, padding=’valid’, data_format=None, activation=None, use_bias=True, kernel_initializer=’glorot_uniform’, bias_initializer=’zeros’, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None) The locally connected layer…
Category:
Deep Learning Tutorial
-
-
Mega Case Study In this mega case study, we are going to make a hybrid deep learning model. As the name suggests,…
-
Keras Merge Layers Add keras.layers.Add() This layer adds a list of inputs by taking a similar shape of the tensors list as…
-
Keras Models Keras has come up with two types of in-built models; Sequential Model and an advanced Model class with functional API.…
-
Recurrent Layers RNN keras.engine.base_layer.wrapped_fn() The RNN layer act as a base class for the recurrent layers. Arguments cell: It can be defined…
-
Recurrent Neural Networks Why not Feedforward Networks? Feedforward networks are used to classify images. Let us understand the concept of a feedforward…
-
Deep Learning Algorithms What is Deep Learning Algorithm? Deep learning can be defined as the method of machine learning and artificial intelligence…
-
Deep Learning Tutorial Deep learning is based on the branch of machine learning, which is a subset of artificial intelligence. Since neural…
-
Keras Sequential Class Sequential class tf.keras.Sequential(layers=None, name=None) The Keras sequential class helps to form a cluster of a layer that is linearly…
-
Artificial Neural Networks At earlier times, the conventional computers incorporated algorithmic approach that is the computer used to follow a set of…