How AI Understands Language | Tokens, Tokenization & Cosine Similarity | NLP in Tamil | Adi Explains скачать в хорошем качестве

How AI Understands Language | Tokens, Tokenization & Cosine Similarity | NLP in Tamil | Adi Explains

If you are searching for a clear and beginner-friendly explanation of Natural Language Processing (NLP) in Tamil, this video is exactly what you need. In this episode of our Deep Learning Series in Tamil, we introduce the foundational concepts that allow AI models to understand human language — tokens, tokenization, embeddings, and semantic similarity using cosine similarity. These ideas form the backbone of modern AI systems like chatbots, search engines, recommendation systems, and large language models. Language is not naturally understandable by machines. Computers do not read sentences the way humans do. Instead, they rely on mathematical representations. This video carefully explains how raw text is transformed step-by-step into numbers that neural networks can process. We begin with the idea of tokens, which are the smallest meaningful units of text. You will learn how a sentence is broken down into tokens and why different tokenization strategies exist depending on the problem being solved. We also discuss why tokenization is not just about splitting by spaces, but about creating a structure that machines can learn from. As the video progresses, we move deeper into tokenization techniques used in NLP. You will understand how traditional word-level tokenization differs from subword and character-level tokenization, and why modern deep learning models prefer subword methods. This concept is explained intuitively in Tamil, making it accessible even if you are new to AI or deep learning. By the end of this section, you will clearly see how sentences become sequences of tokens that can be fed into neural networks. Once tokens are created, the next challenge is meaning. Tokens by themselves do not carry intelligence. This video explains how AI models learn semantic meaning by converting tokens into vectors called embeddings. These embeddings capture context, relationships, and similarities between words and sentences. You will see how words with similar meanings end up closer in vector space, even if they look different in text form. This idea is fundamental to understanding how AI systems “understand” language rather than just memorizing words. A major highlight of this video is the explanation of semantic similarity using cosine similarity. Instead of abstract formulas, we break down the math in a simple and intuitive way, showing how cosine similarity measures the angle between two vectors to determine how similar two sentences are in meaning. This concept is crucial for applications like text search, document matching, question answering systems, and chatbot responses. You will gain clarity on why cosine similarity is preferred over simple distance metrics in NLP tasks. This video is designed especially for Tamil-speaking students, professionals, and self-learners who want to build a strong foundation in AI, machine learning, and deep learning. Whether you are preparing for placements, higher studies, or transitioning into AI roles, understanding these NLP basics will give you a major advantage. The explanations are practical, intuitive, and aligned with how real-world AI systems work today. As part of our Deep Learning Made Easy – Tamil Series, this video acts as a stepping stone toward more advanced topics like transformers, attention mechanisms, BERT, and large language models. If you have ever wondered how ChatGPT-like systems understand queries, compare sentences, or retrieve relevant answers, this video provides the conceptual groundwork. Make sure to watch the video till the end to fully grasp how language is converted into mathematics and how meaning emerges from vectors. If you find this content helpful, do like, share, and subscribe to the channel for more in-depth AI and deep learning tutorials in Tamil. Your support helps us continue creating high-quality educational content for the Tamil tech community. Keywords: NLP in Tamil, tokenization explained in Tamil, tokens in NLP, cosine similarity deep learning, semantic similarity AI, embeddings in NLP, deep learning Tamil, AI language understanding, machine learning Tamil tutorials, NLP basics for beginners, Adi Explains deep learning #python #nlp #datascience #tamil #machinelearning #deeplearning #cosine #naturallanguageprocessing #artificialintelligence #agents #agent #llm #maths #education