📑   Deep Learning. Practice Project 0_0: Image Classification

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In this project, we'll classify images from the Flower Color Images Dataset.
The content is very simple:
603 images (128x128x3) with 20 species of flowering plants stored in the file Flowers128.h5.
In the original dataset, photo files are in the .png format and class labels are integers.
We'll preprocess the images, then train a neural network on all the samples.
The images need to be normalized, shuffled, and divided into three subsets.
We are going to apply Keras: The Python Deep Learning library.
At the end, we'll get to see the neural network's predictions on the sample images.

✒️  Step 0. Import Libraries


✒️  Step 1. Load and Explore the Data



✒️  Step 2. Save the Data


✒️  Step 3. Implement Preprocess Functions


✒️  Step 4. Define the Model


✒️  Step 5. Train the Model



✒️  Step 6. Evaluate and Save the Model


✒️  Step 7. Display Predictions