"sample_image = train_images[0] / 255.0 # Normalize the pixel values\n", "output = nn.forward(sample_image.reshape(1, -1)) # Flatten the image and pass to the network\n", "print(f\"Predicted output: {output}\")" ] },
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\n\n## Reading the Image file\n\nPython supports very powerful tools when it comes to image processing. Let’s see how to process the images using the **PIL** library.\n\nPIL is the Python Imaging Library which provides the python interpreter with image editing capabilities.\n", "...
"![sample output](https://tensorflow.org/images/gan/dcgan.gif)\n", "\n", "To learn more about GANs, we recommend MIT's [Intro to Deep Learning](http://introtodeeplearning.com/) course." ] }, { "cell_type": "markdown", ...
{"cells": [{"cell_type": "markdown", "metadata": {}, "source": "\n \n\n\nData Analysis with Python\n"}, {"cell_type": "markdown", "metadata": {}, "source": "# House Sales in King County, USA\n"}, {"cell_type": "markdown", "metadata": {}, "source": "This ...
"train_dataset = tf.data.Dataset.from_tensor_slices(train_images).shuffle(BUFFER_SIZE).batch(BATCH_SIZE)" ] }, { "cell_type": "markdown", "metadata": { "id": "THY-sZMiQ4UV" }, "source": [ "## 三、创建模型" ] }, { "cell_type": "markdown", "metadata": { "id": "-...
\n\n## Reading the Image file\n\nPython supports very powerful tools when it comes to image processing. Let’s see how to process the images using the **PIL** library.\n\nPIL is the Python Imaging Library which provides the python interpreter with image editing capabilities.\n", "...