45. BLEU Score Explained: Evaluating Machine Translation & NLP Models | In Hindi скачать в хорошем качестве

45. BLEU Score Explained: Evaluating Machine Translation & NLP Models | In Hindi

Bilingual Evaluation Understudy (BLEU) is the industry-standard automatic metric for measuring the quality of generated text. In this video, we break down how BLEU works, from n-gram overlaps to brevity penalties, and where it's used in modern AI. What You’ll Learn: What is BLEU? An overview of the automatic metric used to compare generated text against human reference translations. How it Works: Understanding n-gram overlaps (unigrams, bigrams, etc.) and why they matter for fluency. The Brevity Penalty: How the algorithm discourages overly short outputs to ensure comprehensive results. Key Use Cases: How BLEU is applied in Machine Translation, Text Summarization, Dialogue Systems, and Benchmarking Large Language Models (LLMs). Whether you are studying for an NLP exam or building your own machine-translation system, understanding BLEU is essential for benchmarking model performance. Subscribe for more deep dives into Natural Language Processing and Machine Learning!