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Of course, whether or not you will need to know and use C++ depends on the topics you will research during your Ph.D. or job. If you'll need just to use and/or combine some existing ML models (yes, in a Ph.D., you're expected to come up with new ideas/tools), then you won't probably need to know C++, as the most commonly used libraries for machine learning ...


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I suggest you take a look at Chris Olah's blog. Has several interesting post including ones on visualizing weights and interpretability. Most of his papers also have Google Colab links so you can reproduce the results. If you want something more similar to the model.summary() method you mention, TensorBoard Graph Dashboard might help.


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In my experience, knowledge of any particular programming language does not matter. What matters is that you can quickly pick up the basics of a given language. In my professional work I have been programming in Scala, Java, Groovy, and now Lisp; I didn't really know any of these languages before my working with them (except for Java). But I have been able ...


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