Don’t Learn TensorFlow! Start with Keras or PyTorch Instead

So, you want to learn deep learning? Whether you want to start applying it to your business, base your next side project on it, or simply gain marketable skills – picking the right deep learning framework to learn is the essential first step towards reaching your goal. We strongly recommend that you pick either Keras or PyTorch.

These are powerful tools that are enjoyable to learn and experiment with. We know them both from the teacher’s and the student’s perspective. Piotr has delivered corporate workshops on both, while Rafał is currently learning them.

Keras and PyTorch are open-source frameworks for deep learning gaining much popularity among data scientists. Keras is a high-level API capable of running on top of TensorFlow, CNTK, Theano, or MXNet (or as tf.contrib within TensorFlow). Since its initial release in March 2015, it has gained favor for its ease of use and syntactic simplicity, facilitating fast development.

It’s supported by Google. PyTorch, released in October 2016, is a lower-level API focused on direct work with array expressions. It has gained immense interest in the last year, becoming a preferred solution for academic research, and applications of deep learning requiring optimizing custom expressions.

It’s supported by Facebook. Keras is a high-level API capable of running on top of TensorFlow, CNTK, Theano, or MXNet (or as tf.contrib within TensorFlow). Since its initial release in March 2015, it has gained favor for its ease of use and syntactic simplicity, facilitating fast development.

It’s supported by Google. PyTorch, released in October 2016, is a lower-level API focused on direct work with array expressions. It has gained immense interest in the last year, becoming a preferred solution for academic research, and applications of deep learning requiring optimizing custom expressions.

It’s supported by Facebook.

Source: deepsense.ai