Is Keras still the best choice for Deep Learning in 2026 education?

All answers to this question.

I’ve been teaching Deep Learning for five years, and I’ve found that Keras is the best way to keep students engaged. If you start with raw PyTorch or NumPy, many students get bogged down in syntax errors and lose sight of the actual neural network concepts. Keras 3 is perfect because it follows the principle of "progressive disclosure of complexity." You can start with the Sequential API for the first two weeks, then move to the Functional API, and eventually have them write custom layers and training loops using keras.ops. This way, they learn the high-level logic first and dive into the math only when they have a mental framework to hold it.

   Answered 2025-03-15 by Cynthia Lewis

Do you think that by starting with Keras, students might struggle later when they have to read academic papers that almost exclusively use PyTorch code for their implementations?

   Answered 2025-05-20 by Raymond Scott

• Raymond, that used to be a concern, but Keras 3 actually helps bridge that gap. Since a Keras model can be instantiated as a PyTorch module, students can take a Keras model they built and literally drop it into a PyTorch-based research paper's code. This "bilingual" capability is much better for their education than forcing them to pick one side of the "framework wars."

     Commented 2025-05-25 by Edward King

Keras CV and Keras NLP are also great for teaching. They provide high-level components for state-of-the-art models that would take weeks to build from scratch.

   Answered 2025-07-12 by Gary Wilson

• Exactly, Gary. Using KerasCV to teach object detection allows students to actually see a working model in a single lab session, which is much more motivating than spending three weeks just trying to get the data loader to work.

     Commented 2025-07-20 by Cynthia Lewis