Hi guys, posting for my brother .
Thought I’d take some advice from Blind fam who are into Natural Language Processing. Since this isn’t my Masters area of specialization.. I wanted to take advice from subject matter experts.
This is his query in his own words
.....
I recently started learning Natural Language Processing as a part of my academic project. My project involves understanding the existing techniques and methods used in estimating Semantic Similarity of short texts and see if there's any possibility to optimise or come up with a better approach. It's kind of like a research based project. So I need to implement my approach on a standard dataset for performance evaluation.
What would be the best sources to help me understand the concepts and implementation using Python. Are there any books, courses, YouTube channels and blogs that can be helpful?
......
My understanding is that he is looking for advice on the resources, a right starting point and approach .
Appreciate any help !
My tc : 187k
Yoe : 3
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comments
Dataset - Twitter (fits the short text stuff)
Task - loads of possible tasks - easiest is sentiment analysis. More difficult - expansion of tweet to full sentence by expanding all hashtags to words, replaces jargons with full form, etc
Methods/library : try Gensim, it's my fav library for text analysis. You can do LDA, W2v, d2v, and tons of other things!
Hope it helps :)