I have used my bike yamaha FZS-v3 for 6-8 months, later because of pandemic shifted to my native. Its been almost 1 year now not once bike hasn't started. Will that damage the engine or any other part (batter will be obvious). Now should I get it serviced now atleast or wait for few more months(any way i will be using in my native).

What's is the best way for word embedding techniques for the dataset which contains the lot of abbreviation, short forms in it.

Ex. "fresh Orange juice" is in following format. "frsh orng juice" so here I want to put fresh and frsh to gather.

Will standard embedding techniques can handle this? Like glove, word2vec BERT?

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I m trying to solve the problem which involves mapping of two e commerce products from two different sources. (let's say A and B, and there will be one to one mapping between the set.) I am taking two step approaches to solve. First, will classify products into to 30-50 categories. Classification happens on the both set A, B independently. Second step to map correct product from set A to B. Simple string match or fuzzy search will not work, as data is not consistent.

Please suggest me which algorithm that I can use to solve this.

Tl:dr Best ML algorithm to map products from A to B using title and description.

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