Fastest way to develop a custom translation model with RNN?

I’m a Python web developer, so I have some professional coding
experience, but I’m a complete novice when it comes to machine

In short, I have a dataset (csv form) with 65,000 sentences in
two languages. One of the languages is real, the other is not. I’d
live to quickly dive into an RNN example online so that I can train
a model based on this dataset, but all of the examples seem to
prefer that I use existing, binary datasets (that I can’t

My laptop is relatively old, and processing a dataset properly
can take a week, so every example I’ve attempted to adapt to my
needs has cost lots of time and lots of heartache when I discover
that I can’t use it.

Is there an RNN translation tutorial that anyone would recommend
for the purpose of translating between an existing corpus and a
constructed language? I can do research on any terms listed below,
but the topic of machine learning has so regularly stumped me that,
even though I know easy examples for what I want to do probably
already exist, I don’t even know where to start.

Thank you for your time!

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