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You can not build a topic modelling pipeline if you're looking for the wrong vectors into your clustering algorithm. Individual word embeddings will lose the context of the document. To group text ef
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Do you really understand what your customers want from you? AI isn't just for writing emails. With proper topic modelling you can automatically ingest thousands of reviews and classify them into clea
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Think you need a CS degree to work in AI? No, you don't. The industry has shifted. The reality is that a massive wave of non- tech and non-coding roles is here. Maths,coding,tech fields are not the
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Just because you have access to a massive decoder model doesn't mean it is the right architectural choice for your pipeline. Topic modelling requires deep contextual understanding,which is exactly wh
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If TF-IDF is your go-to answer for text clustering in a technical interview then,you are going to get rejected. The industry has moved on. Traditional methods fail completely when faced with short te
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I see small businesses wasting thousands on "Custom AI" that could have been handled by a simple open-source Encoder model. Don't let technical jargon bleed your budget dry. Get a solution that focus
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AI is not magic. It's engineering, and engineering is just solving problems with the right tools Whether you want to be a Data Analyst or an ML Engineer,these three architectures are your foundation
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Will AI make you 'obsolete' ? No, if you keep your fundamentals strong then AI won't replace you. If you are from a testing background then I assure you that your experience and knowledge is an asset
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Using a massive Decoder-only model for simple semantic search is like using a sledgehammer to hang a picture frame. It works,but it's expensive and inefficient. Senior AI engineers choose the variant
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Do you think that "GPT is the best for everything"? If you say that in an interview,then that is a one-way ticket to a rejection email. Understanding whether a model is Encoder-only or Decoder-only
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Are you trying to build a LLM from scratch? Stop!!! If you want to ride the AI wave,you do not need to understand every single component of a LLM or dive deep into research papers. The industry hire
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After running our data through all the decoder blocks,we are left with a massive vector of raw numbers.But the AI needs to predict an actual human language word not a number. Here comes the linear la
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About @unfold_data_science

Aman Kumar| AI, ML, Data Science, Generative AI Explained is a Instagram micro influencer. With 12.4K followers and 12 posts, unfold_data_science's account shows a follower-to-following ratio of 414.6:1. This profile demonstrates strong community engagement within its niche. View all content anonymously on Pictame - no login required.

unfold_data_science's engagement rate sits at 0.03%. For accounts with 10K-100K followers, the average is around 2.5%, so there's some room to grow — though every community is unique.

Out of the last 12 posts, 17% are videos and 83% are photos. Notably, videos tend to get 1.5x more engagement than photos. New content goes up pretty much every day — a very consistent posting habit. Captions lean moderate, averaging 470 characters.

0.03% engagement rate — room to grow compared to average for 10K-100K follower accounts.
17% videos, 83% photos. Videos get 1.5x more engagement here.
Posts every day — very consistent.
414.6:1 follower-to-following ratio.

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@unfold_data_science

Aman Kumar| AI, ML, Data Science, Generative AI Explained

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