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All the feature columns of the dataset can be viewed using Tensorflow and Estimator with the help of the ‘DenseFeatures’ method. This data is converted into Numpy array so that it can be viewed on the console.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 More
Tensorflow can be used with Estimator to transform the feature column by first converting the first row of the dataset into a dictionary, and then uses one-hot encoding to transform this feature column, i.e. the ‘gender’ 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 More
Tensorflow can be used with Estimators to create feature columns and input functions by using one-hot encoding method. The ‘feature_column.indicator_column’ is used to return the output of this one-hot encoding technique.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 ... Read More
Tensorflow can be used with Estimators to visualise the plot of number of males versus females with the help of ‘matplotlib’ library and ‘show’ 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 to build learning ... Read More
Tensorflow can be used with Estimators to determine data about the class to which every passenger in the titanic dataset belongs to, with the help of the ‘value_counts’ method. This data is visualized as a horizontal bar graph.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 ... Read More
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 More
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 More
Boosted trees with Tensorflow can be used to show a sample of the titanic dataset using the ‘head’ method, the ‘describe’ method and the ‘shape’ method. The head method gives the first few rows of the dataset, and the describe method gives information about the dataset, such as column names, types, mean, variance, standard deviation and so on. The shape method gives the dimensions of the data.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 ... Read More
Tensorflow can be used with boosted trees to improve the prediction performance of the dataset. The data is loaded, and pre-processed in the way it is usually done, but when the predictions are made, multiple models are used for the predictions, and the output of all these models is combined to give the final result.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 ... Read More
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 More