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This dataset consists of over 170 labeled images of birds, including validation images. Each image belongs to only one bird category. The challenge is to develop models that can accurately classify these images into the correct species.
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### 📚 Libraries Needed
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- os - Provides functions to interact with the operating system.
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- shutil - Offers file operations like copying, moving, and removing files.
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- time - Used for time-related functions.
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- torch - Core library for PyTorch, used for deep learning.
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- torch.nn - Contains neural network layers and loss functions.
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- torchvision - Provides datasets, models, and image transformation tools for computer vision.
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- torchvision.transforms - Contains common image transformation operations.
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- torch.optim - Optimizers for training neural networks.
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- matplotlib.pyplot - Used for data visualization, like plotting graphs.
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## EDA Result 👉 [Classified Bird Species](https://github.com/Archi20876/machine-learning-repos/blob/main/Classification%20Models/Bird%20species%20classification/bird-species-classification.ipynb)
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