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Articles by AmitDiwan
Page 698 of 840
How Tensorflow be used for the gender column, like feature column helping in prediction?
The ‘gender’ column will be used in the prediction as well, hence it is important to understand more about it. This can be done by visualizing the ‘age’ column as a horizontal bar plot.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We ...
Read MoreHow can Tensorflow be used with Estimators to display metadata about the dataset?
Metadata about the dataset can be displayed using the ‘describe’ method, as well as by visualizing the dataset, with specific statistic. The ‘hist’ method can be used to visualize a histogram with respect to a specific column.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a ...
Read MoreHow can Tensorflow be used with Estimators to visualize the data, and the ROC curve?
The titanic dataset model can be visualized and the ROC curve can be visualized to understand the performance with the help of the ‘matplotlib’ and ‘roc_curve’ (which is present in the ‘sklearn.metrics’ module) methods respectively.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. ...
Read MoreHow can Tensorflow be used with Estimators to optimize the model?
The model associated with titanic dataset can be optimized to give better performance after the specific columns are added. Once the columns are added, and trained, and the model is evaluated, the model will be trivially optimized, thereby giving better performance.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer ...
Read MoreHow can Tensorflow be used with Estimators to add a column to the titanic dataset?
A column can be added to the titanic dataset using Tensorflow by using the ‘crossed_column’ method which is present in the ‘feature_column’ class of ‘Tensorflow’ module. The model can be trained again using the ‘train’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional ...
Read MoreHow can Tensorflow be used with Estimators to perform data transformation?
Data transformation can be performed on the titanic dataset with the help of the ‘DenseFeatures’ method. The columns that need to be transformed, are converted into a Numpy array.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural ...
Read MoreHow can Tensorflow be used with Estimators to inspect a specific column of titanic dataset?
A specific column in the titanic dataset can be inspected by accessing the column-to-be-inspected and using the ‘DenseFeatures’ and converting it into a Numpy array.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.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 ...
Read MoreHow can Tensorflow be used with Estimators to define a function that shuffles data?
A function that shuffles data can be defined, with the help of estimators. A dictionary is created that stores the data. This is done using the ‘from_tensor_slices’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network ...
Read MoreHow can Tensorflow Hub be used to fine-tune learning models?
TensorFlow Hub is a repository that contains trained machine learning models. These models are ready to be fine-tuned and deployed anywhere. The trained models such as BERT and Faster R-CNN can be reused with a few lines of code. It is an open-repository, which means it can be used and modified by anyone.The tfhub.dev repository contains many pre-trained models. Some of them include text embeddings, image classification models, TF.js/TFLite models and so on.It can be installed using the below code:!pip install --upgrade tensorflow_hubIt can be imported into the working environment as shown in the below code:import tensorflow_hub as hub
Read MoreHow can a customized model be pre-trained?
A sequential model can be built using Keras Sequential API that is used to work with plain stack of layers. Here every layer has exactly one input tensor and one output tensor.A pre-trained model can be used as the base model on the specific dataset. This saves the time and resources of having to train the model again on the specific dataset.A pre-trained model is a saved network which would be previously trained on a large dataset. This large dataset would be a large-scale image-classification task. A pre-trained model can be used as it is or it can be customized ...
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