@ -313,7 +313,16 @@ Javascript has a rich set of cross-platform mobile app development tools such as
TIP: Machine learning with Node.js is fairly new, but it is fast evolving because there is growing interest in adding machine learning capabilities to web and mobile applications.
TIP: Machine learning with Node.js is fairly new, but it is fast evolving because there is growing interest in adding machine learning capabilities to web and mobile applications.
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=== Reasons to learn machine learning with Python - PyTorch
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*Python is better suited for server-side training of machine learning models*
It can scale and distribute its load on server clusters to accelerate the training process. Once the model is trained, you can compress it and deliver it on user devices for inference. Fortunately, machine learning libraries written in different languages are highly compatible.
For instance, if you train your deep learning model with TensorFlow or Keras for Python, you can save it in one of several language-independent formats such as JSON or HDF5. You can then send the saved model to the user’s device and load it with TensorFlow.js or another JavaScript deep learning library.