From a82e4f1196e7576fad1b930b98ca5be198ac717e Mon Sep 17 00:00:00 2001 From: zeus Date: Tue, 7 Dec 2021 00:02:20 +0200 Subject: [PATCH] tech list --- tech-list/modules/ROOT/pages/index.adoc | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/tech-list/modules/ROOT/pages/index.adoc b/tech-list/modules/ROOT/pages/index.adoc index a1edf55..0e2c5b0 100644 --- a/tech-list/modules/ROOT/pages/index.adoc +++ b/tech-list/modules/ROOT/pages/index.adoc @@ -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. +==== + +=== Reasons to learn machine learning with Python - PyTorch + +==== +*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. ====