Which is better: TensorFlow, PyTorch or Keras?

None is universally better. TensorFlow and PyTorch are full frameworks, while Keras 3 is a high-level API that runs on TensorFlow, PyTorch or JAX. Choose using a representative model, deployment target, quality metrics, performance, team capability and lifecycle cost.

Is Keras a deep learning framework?

Keras 3 is best described as a multi-backend deep-learning API. It supplies model-building and training abstractions but relies on TensorFlow, PyTorch or JAX as its backend runtime.

Is TensorFlow a framework?

Yes. TensorFlow is an end-to-end machine-learning framework with tensor operations, automatic differentiation, training, distribution and a wider production ecosystem including TFX and serving targets.

Is PyTorch or Keras better for beginners building neural networks?

Keras often gets a standard model to a readable baseline faster. PyTorch can be better when the learner needs direct control over training loops or will join a PyTorch codebase. A beginner should still learn data splits, error analysis, reproducibility and deployment constraints.

Can Keras use PyTorch and TensorFlow?

Yes. Keras 3 supports TensorFlow, PyTorch and JAX backends. Portable models should prefer built-in Keras layers and keras.ops; backend-specific operations can make a component dependent on one backend.

Should scikit-learn be included in a deep learning framework comparison?

Include it as a classical or small-MLP baseline when appropriate, not as an equivalent deep-learning platform. Scikit-learn's maintainers explicitly place complex deep learning outside the library's scope.

Persian · Rusaka

مقایسه چارچوب های یادگیری عمیق محبوب: TensorFlow در مقابل PyTorch در مقابل Keras

در زمینه به سرعت در حال تکامل هوش مصنوعی، چارچوب های یادگیری عمیق نقش مهمی در توسعه شبکه های عصبی ایفا می کنند. این مقاله سه مورد از محبوب ترین چارچوب های یادگیری عمیق را مقایسه می کند: TensorFlow، PyTorch و Keras، برجسته کردن ویژگی های منحصر به فرد و استفاده از موارد.