Building deep learning models is just the beginning—refining them is where the magic happens. In this episode, we take you through a hands-on journey with TensorFlow, Keras, and PyTorch, tackling real-world tasks like image classification and sentiment analysis. We’ll uncover debugging strategies to spot what’s holding your model back, then dive into optimization techniques—tuning learning rates, adding regularization, leveraging batch normalization, and experimenting with optimizers. Whether you’re troubleshooting or scaling up, this episode equips you with a clear workflow to conquer deep learning challenges.