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Python Articles
Page 769 of 855
How can Tensorflow be used to explore the flower dataset using keras sequential API?
The flower dataset can be explored using the keras sequential API with the help of the ‘PIL’ package and the ‘Image.open’ method. Different subdirectories have different types of images of flowers, which can be indexed and displayed on the console.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.An image classifier is created using a keras.Sequential model, and ...
Read MoreHow can Tensorflow be used to evaluate a CNN model using Python?
A convolutional neural network can be evaluated using the ‘evaluate’ method. This method takes the test data as its parameters. Before this, the data is plotted on the console using ‘matplotlib’ library and ‘imshow’ methods.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. 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 train and compile a CNN model?
A convolutional neural network can be trained and compiled using the ‘train’ method and the ‘fit’ method respectively. The ‘epoch’ value is provided in the ‘fit’ 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. Convolutional neural networks have been used to produce ...
Read MoreHow can Tensorflow be used to add dense layers on top using Python?
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 MoreHow can Tensorflow be used to create a convolutional base using Python?
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 MoreHow can Tensorflow and Python be used to verify the CIFAR dataset?
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 MoreHow can Tensorflow and Python be used to download and prepare the CIFAR dataset?
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 MoreHow can Tensorflow used to segment word code point of ragged tensor back to sentences?
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 MoreHow can Tensorflow and Python be used to build ragged tensor from list of words?
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 MoreHow can Tensorflow and Python be used to get code point of every word in the sentence?
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 ...
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