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Server Side Programming Articles - Page 1262 of 2650
 
 
			
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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
 
 
			
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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
 
 
			
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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
 
 
			
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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
 
 
			
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The UTF-8 strings can be split using Tensorflow text. This can be done with the help of ‘UnicodeScriptTokenizer’. ‘UnicodeScriptTokenizer’ is a tokenizer that is created, after which the ‘tokenize’ method present in ‘UnicodeScriptTokenizer’ 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 ... Read More
 
 
			
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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
 
 
			
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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