Feb 9 · 6 min read · Hello 😊, We learned the core philosophy behind BERT in the introductory chapter of our previous series chapter. In this chapter, we’ll learn more about BERT and another pivotal process in Machine Learning known as General Language Pre-training, GLP....
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Aug 11, 2025 · 1 min read · Here is the third installment of the AI Sketchbook Series, where we demystify fundamental AI concepts with a semi-visual approach. In our previous posts, we explored how to represent text using One-Hot Encoding and the Bag-of-Words TF-IDF method. Whi...
Join discussionApr 15, 2025 · 3 min read · So during one of my early NLP experiments, I came across a massive dataset of Amazon product reviews, and thought — can I train a model to automatically detect whether a review is positive, negative, or neutral? I knew that many people had done senti...
Join discussionApr 13, 2025 · 8 min read · 📌 What is Text Vectorization? In NLP, machines can’t understand text directly — they understand numbers. Text vectorization is the process of converting textual data into numerical vectors so that we can feed them into machine learning or deep learn...
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Feb 9, 2025 · 12 min read · Introduction Have you ever wondered how machines understand human language? How does Google suggest search queries even before you finish typing? How do chatbots comprehend user queries and generate relevant responses? The secret lies in word embeddi...
Join discussionJan 24, 2025 · 4 min read · Introduction Imagine walking into a library that has no labels or categories. All the books are just randomly placed on shelves. Finding a book you like would take forever, right? But what if we could arrange the books in a way where similar ones are...
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Dec 1, 2023 · 2 min read · Note: BERT is designed for contextual embeddings. Creating static embedding from BERT therefore defeats its purpose. [1] Install Required Libraries Ensure that the necessary libraries installed i.e. torch, gensim, numpy, and transformers (Hugging Fac...
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Nov 16, 2023 · 8 min read · What is Word Embedding ? In Natural Language Processing , word embedding is a term used for the representation of words for text analysis , typically in the form of real valued vectors that encodes the meaning of the word such that the words that are...
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Oct 31, 2023 · 5 min read · Introduction Word embeddings have become a foundational technology in Natural Language Processing (NLP), providing a way to represent words and documents in a numerical format. In this blog post, we'll explore the use of word embeddings in the contex...
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