Скачать или смотреть TF-idf Vectorizer | Feature Extraction | Machine Learning

code: https://github.com/sudip125/Tfidf_vec...

00:00 -- Why TF-idf ?
06:53 -- Two term in Tf-idf vectorizer
30:38 -- Coding part

Welcome to our channel, where we delve into the fascinating world of machine learning! In this video, we'll be diving deep into TF-IDF vectorizer, a powerful technique widely used in natural language processing (NLP) tasks. Whether you're a beginner or an experienced practitioner, this guide will equip you with the knowledge you need to harness the potential of TF-IDF vectorization in your own projects.

TF-IDF (Term Frequency-Inverse Document Frequency) is a numerical statistic that reflects the importance of a term within a document or a corpus. By calculating the TF-IDF score for each term, we can effectively identify the significance of words in a collection of texts. This information is invaluable in various applications such as text classification, information retrieval, and sentiment analysis.

By the end of this video, you'll have a solid understanding of TF-IDF vectorization and how it can elevate the performance of your machine learning models in NLP tasks. Don't forget to subscribe to our channel for more exciting content on machine learning, AI, and data science. Let's dive in and unlock the potential of TF-IDF together!

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