Prompt

I am learning machine learning and neural networks, specifically focusing on building a neural network from scratch to classify images of dogs and cats. Please provide detailed guidance on the following: 1. Recommended state-of-the-art neural network architectures suitable for this task (e.g., CNNs). 2. Data sources for obtaining labeled dog and cat images, including any public datasets. 3. Step-by-step instructions on how to preprocess the images for training. 4. Example code snippets for implementing the neural network using a popular framework (e.g., TensorFlow or PyTorch). 5. Common pitfalls and edge cases to consider, such as overfitting and data imbalance, along with strategies to mitigate them. Define success criteria for the model's performance, such as accuracy metrics and validation techniques.