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Articles by AmitDiwan
Page 694 of 840
Difference Between Flood-fill and Boundary-fill Algorithm
In this post, we will understand the differences between flood fill algorithm and boundary fill algorithm. They are area-filling algorithms, and they can be differentiated based on whether a random pixel has the region's original colour or not.Flood-fill algorithmIt is also known as seed fill algorithm.It calculates the area that is connected to a given node with respect to a multi-dimensional array.It works by filling up or recolouring a specific area that contains different colours in the inside part, and hence, the boundary of the image.It is represented by a picture that has a neighbourhood which has borders and has ...
Read MoreDifference Between Greedy Method and Dynamic Programming
In this post, we will understand the differences between the greedy algorithm and dynamic programming methods.Greedy algorithmIt is an algorithmic paradigm that builds up on a solution in parts, step by step. The next step is chosen such that it gives the most obvious and immediate benefit.Problems that involve choosing local optimal values will help in choosing the global optimal values/solution to the problem. Such ate the problems associated with greedy algorithm.There is no surety that a greedy algorithm would lead to an optimal solution.An optimal choice is made at every stage of the problem, i.e the local optimal solution.It ...
Read MoreDifference Between Prim's and Kruskal's Algorithm
In this post, we will understand the differences between Prim's and Kruskal's algorithms.Kruskal's algorithm for Mininum Spanning Tree (MST)When a connected and undirected graph is given, a spanning tree of such a graph is the subgraph which is a tree that connects all of the vertices.A single graph can have multiple spanning trees.A minimum spanning tree (MST) (also known as minimum weight spanning tree) for a weighted, connected and undirected graph is a spanning tree that weighs less than or equal to the weight of every other spanning tree.The weight of a spanning tree is determined by adding the weights ...
Read MoreHow can TensorFlow be used with keras.Model to track the variables defined using sequential model?
Tensorflow can be used to create a model that tracks internal layers by creating a sequential model and using this model to call ‘tf.zeros’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model for the visual world. It ...
Read MoreHow can Tensorflow be used to implement custom layers?
Tensorflow can be used to implement custom layers by creating a class and defining a function to build the layers, and defining another function to call the matrix multiplication by passing the input to it.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively ...
Read MoreHow can Tensorflow be used to get the variables in a layer?
Tensorflow can be used to get the variables in a layer by displaying the variables in the layer using ‘layer.Variables’, and then using ‘layer.kernel’, and ‘layer.bias’ to access these variables.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model ...
Read MoreHow can Tensorflow be used to confirm that the saved model can be reloaded, and would give same results?
Tensorflow can be used to confirm that the saved model can be reloaded by using the ‘load_model’ and using the ‘predict’ method. The reloaded model can be used predict the data.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic ...
Read MoreHow can Tensorflow be used to export the model so that it can be used later?
Tensorflow can be used to export the model so that it can be used later by first saving the model using ‘save’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model for the visual world. It would have ...
Read MoreHow can TensorFlow be used to visualise the trade off between accuracy and training steps?
Tensorflow can be used to visualize the trade-off between accuracy and training steps using the ‘matplotlib’ library and ‘plot’ method to plot the data.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model for the visual world. It would ...
Read MoreHow can Tensorflow be used to run the classifier on a batch of images?
TensorFlow be used to run the classifier on a batch of images using the ‘classifier’ class, and ‘predict’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model. The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model for the visual world. It would have learned the feature maps, ...
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