Technical words extractor Neural Network model

I want to have a Deep Learning (Neural Network) model that can extract all technical words from an article.

Help and guidance can be found at:

- [login to view URL]

- [login to view URL]@nikkisharma536/white-paper-job-skills-extraction-with-lstm-and-word-embeddings-d71d1f96024f with [login to view URL]

I want it to be done with Python. I want the code to be WELL DOCUMENTED.

YOU will have to find some training / testing dataset as well.

The input I believe will be .pdf files that you will parse and the output can be printed on the console. I can modify that later.

I want to have train() and test() methods. The model will be saved when I will train() the network on the dataset and loaded when I will test() it.

The output needs to be exactly (or maybe better) as the one from here [login to view URL]

As EXAMPLE for "I used C++ over QT Framework in order to get a nice GUI for what will be further be an Django Project with Python etc" the output should be [C++, QT Framework, GUI, Django, Python]

Thank you!

Python Dolování dat Machine Learning (ML) Softwarová architektura Sběr dat z webových stránek

Identifikační číslo projektu: #22431497

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