A hands-on comparison of performance, flexibility, and developer experience using CIFAR-10 A few days ago, I set out to build a simple image classification model using Convolutional Neural Networks (CNNs). The task itself wasn't particularly complex, but choosing the right framework proved more challenging than expected. I found myself choosing between TensorFlow and PyTorch, two powerful frameworks for building high-performance CNNs. To explore this, I implemented the same CNN in both frameworks under identical conditions and compared them across key aspects like learning curve, flexibility, debugging, and performance. A Quick Look at the Frameworks Before deep diving into the comparison, it's worth briefly understanding the two frameworks used throughout this experiment. 1. TensorFlow TensorFlow is an open-source deep learning framework developed by Google. It is widely known for its strong ecosystem and production-ready capabilities.…