Found 178 Articles for Tensorflow

A dense layer can be added to the sequential model using the ‘add’ method, and specifying the type of layer as ‘Dense’. The layers are first flattened, and then a layer is added. This new layer will be applied to the entire training dataset.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.We are using the Google Colaboratory ... Read More

A convolutional neural network would generally consist of combination of the following layers: Convolutional layers, Pooling layers and Dense layers.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Convolutional neural networks have been used to produce great results for a specific kind of problems, such as image recognition. It can be created using the ‘Sequential’ method which is present in the ‘models’ class. Layers can be added to this convolutional network using the ‘add’ method.We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with ... Read More

The CIFAR dataset can be verified by plotting the images present in the dataset on the console. Since the CIFAR labels are arrays, an extra index would be needed. The ‘imshow’ method from the ‘matplotlib’ library is used to display the image.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?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 Processing Units). Colaboratory has been built on top of Jupyter Notebook.print("Verifying the data") ... Read More

The CIFAR dataset can be downloaded using the ‘load_data’ method which is present in the ‘datasets’ module. It is downloaded, and the data is split into training set and validation set.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 aconvolutional layer. A convolutional neural network would ... Read More

The word code point of a ragged tensor can be segmented in the following method: 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.The word’s code point is segmented back to sentence. The next step is to check if the code point for a character in a word is present in the sentence or ... Read More

A RaggedTensor can be built by using the starting offsets of the words in the sentence. Firstly, the code point of every character in every word in the sentence is built. Next, they are displayed on the console. The number of words in that specific sentence is determined, and the offset is determined.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?Represent Unicode strings using Python, and manipulate those using Unicode equivalents. At first, we will separate the Unicode strings into tokens based on script detection with the help of the Unicode equivalents of standard ... Read More

To get the code point of every word in a sentence, it is first checked to see if sentence is the start of the word or not. Then, it is checked to see if index of character starts from specific index of word in the flattened list of characters from all sentences. Once this is verified, the code point of every character in every word is obtained by using the below method.The script identifiers help determine the word boundaries and the location where should be added. Word boundary is added at the beginning of a sentence and for each character ... Read More

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 More

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 More

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 More