Found 178 Articles for Tensorflow

Character substrings can be used with Tensorflow using the ‘substr’ method which is present in ‘strings’ module of Tensorflow. It is then converted into a Numpy array and then displayed.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will see how to represent Unicode strings using Python, and manipulate those using Unicode equivalents. First, separate the Unicode strings into tokens based on script detection with the help of the Unicode equivalents of standard string ops.We are using the Google Colaboratory to run the below code. Google Colab or Colaboratory helps run Python code over ... Read More

Unicode operations can be performed by first fetching the length of the strings, and setting this to other values (the default value is ‘byte’). The ‘encode’ method is used to convert vector of code points into encoded string scalar. This is done to determine the Unicode code points in every encoded string.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Models which process natural language handle different languages that have different character sets. Unicode is considered as the standard encoding system which is used to represent character from almost all the languages. Every character is ... Read More

Multiple strings of same length can be encoded using the ‘tf.Tensor’ as an input value. When encoding multiple strings of varying lengths need to be encoded, a tf.RaggedTensor should be used as an input. If a tensor contains multiple strings in padded/sparse format, it needs to be converted to a tf.RaggedTensor. Then, the method unicode_encode should be called on it.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Let us understand how to represent Unicode strings using Python, and manipulate those using Unicode equivalents. First, we separate the Unicode strings into tokens based on script ... Read More

A set of Unicode strings can be represented as UTF8-encoded string using the ‘encode’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Models which process natural language handle different languages that have different character sets. Unicode is considered as the standard encoding system which is used to represent character from almost all the languages. Every character is encoded with the help of a unique integer code point that is between 0 and 0x10FFFF. A Unicode string is a sequence of zero or more code values.Let us understand how to represent Unicode strings using Python, ... Read More

The encoded string scalar can be converted to a vector of code points using the ‘decode’ method. The vector of code points can be converted to an encoded string scalar using the ‘encode’ method. The encoded string scalar can be converted to a different encoding using the ‘transcode’ method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Let us understand how to represent Unicode strings using Python, and manipulate those using Unicode equivalents. First, we separate the Unicode strings into tokens based on script detection with the help of the Unicode equivalents of standard string ... Read More

Unicode strings are utf-8 encoded by default. Unicode string can be represented as UTF-8 encoded scalar values using the ‘constant’ method in Tensorflow module. Unicode strings can be represented as UTF-16 encoded scalar using the ‘encode’ method present in Tensorflow module.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Models which process natural language handle different languages that have different character sets. Unicode is considered as the standard encoding system which is used to represent character from almost all the languages. Every character is encoded with the help of a unique integer code point that ... Read More

Training and building the model with respect to the abalone data can be done using the ‘compile’ and ‘fit’ methods respectively. The ‘fit’ method also takes the number of epochs as the parameter.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will be using the abalone dataset, which contains a set of measurements of abalone. Abalone is a type of sea snail. The goal is to predict the age based on other measurements.We are using the Google Colaboratory to run the below code. Google Colab or Colaboratory helps run Python code over the browser ... Read More

A normalization layer can be built using the ‘Normalization’ method present in the ‘preprocessing’ module. This layer is made to adapt to the features of the abalone dataset. In addition to this, a dense layer is added to improve the training capacity of the model. This layer will help pre-compute the mean and variance associated with every column. This mean and variance values will be used to normalize the data.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will be using the abalone dataset, which contains a set of measurements of abalone. Abalone is ... Read More

A sequential model can be built in Keras using the ‘Sequential’ method. The number and type of layers are specified inside this method.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will be using the abalone dataset, which contains a set of measurements of abalone. Abalone is a type of sea snail. The goal is to predict the age based on other measurements.We are using the Google Colaboratory to run the below code. Google Colab or Colaboratory helps run Python code over the browser and requires zero configuration and free access to GPUs (Graphical ... Read More

Once the abalone dataset has been downloaded using the google API, a few samples of the data can be displayed on the console using the ‘head’ method. If a number is passed to this method, that many rows would be displayed. It basically displays the rows from the beginning.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will be using the abalone dataset, which contains a set of measurements of abalone. Abalone is a type of sea snail. The goal is to predict the age based on other measurements.We are using the Google Colaboratory ... Read More