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Found 178 Articles for Tensorflow
123 Views
A two-element tuple can be returned by processing iris flower dataset by creating a method that takes the features and labels, and returns them as Numpy arrays.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 ... Read More
115 Views
The key features/column names from the iris dataset can be extracted, by deleting the irrelevant features. This can be done using the ‘pop’ 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 model. TensorFlow ... Read More
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Tensorflow can be used with premade estimator to download the iris dataset using the ‘get_file’ method present in Keras package. A Google API holds the iris dataset, which can be passed as parameter to the ‘get_file’ 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 ... Read More
193 Views
Tensorflow text can be used with whitespace tokenizer by calling the ‘WhitespaceTokenizer’’, which creates a tokenizer, that is used with the ‘tokenize’ method on the string.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 ... Read More
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The ‘wordshape’ method can be used along with specific conditions such as ‘HAS_TITLE_CASE’, ‘IS_NUMERIC_VALUE’, or ‘HAS_SOME_PUNCT_OR_SYMBOL’ to see if a string has a particular property.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
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The ‘tf.data’ API can be used to tokenize the strings. Tokenization is the method of breaking down a string into tokens. These tokens can be words, numbers, or punctuation.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 More
114 Views
The ‘UnicodeScriptTokenizer’ can be used to tokenize the data. The start and end offsets of every word in each sentence can be obtained.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 model. TensorFlow Text ... Read More
382 Views
Tensorflow text can be used to split the strings by character using ‘unicode_split’ method, by first encoding the split strings, and then assigning the function call to a variable. This variable holds the result of the function call.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
166 Views
Tensorflow text can be used to tokenize string data with the help of the ‘WhitespaceTokenizer’ which is a tokenizer that is created, after which the ‘tokenize’ method present in ‘WhitespaceTokenizer’ is called on the string.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
138 Views
Tensorflow text is a package that can be used with the Tensorflow library. It has to be installed explicitly before using it. It can be used to pre-process data for text-based models.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 ... Read More
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