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Tensorflow Articles
Page 13 of 15
What is segmentation with respect to text data in Tensorflow?
Segmentation refers to the act of splitting text into word-like units. This is used in cases where space characters are utilized in order to separate words, but some languages like Chinese and Japanese don’t use spaces. Some languages such as German contain long compounds that need to be split in order to analyse their meaning.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. ...
Read MoreWhat are uncide scripts with respect to Tensorflow and Python?
Every Unicode code point belongs to a single collection of codepoints which is known as a script. A character's script determines the language to which the character would belong. TensorFlow comes with ‘strings.unicode_script’ method that helps find which script would be used by a given codepoint. The script codes are int32 values which can be mapped to International Components for Unicode (ICU) UScriptCode valuesRead More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will no see how to represent Unicode strings using Python, and manipulate those using Unicode equivalents. First, separate the Unicode strings into ...
Read MoreHow can Unicode string be split, and byte offset be specified with Tensorflow & Python?
Unicode string can be split, and byte offset can be specified using the ‘unicode_split’ method and the ‘unicode_decode_with_offsets’methods respectively. These methods are present in the ‘string’ class of ‘tensorflow’ module.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?To begin, represent Unicode strings using Python, and manipulate those using Unicode equivalents. 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 the browser and requires ...
Read MoreHow can Tensorflow be used to work with character substring in Python?
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 MoreHow to encode multiple strings that have the same length using Tensorflow and Python?
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 MoreHow can Tensorflow be used in the conversion between different string representations?
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 MoreHow can Unicode strings be represented and manipulated in Tensorflow?
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 MoreHow can Tensorflow be used to build a normalization layer for the abalone dataset?
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 MoreHow can Tensorflow be used with abalone dataset to build a sequential model?
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 MoreHow can Tensorflow be used to load the csv data from abalone dataset?
The abalone dataset can be downloaded by using the google API that stores this dataset. The ‘read_csv’ method present in the Pandas library is used to read the data from the API into a CSV file. The names of the features are also specified explicitly.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 ...
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