Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Learn the fundamentals of Natural Language Processing through this comprehensive Hindi-language tutorial series covering essential concepts and techniques. Explore basic NLP terminologies and understand core preprocessing steps including tokenization for breaking text into meaningful units, stopwords removal for filtering common words, stemming for reducing words to root forms, and lemmatization for converting words to their base dictionary forms. Master feature extraction methods such as Bag of Words (BoW) for text representation and TF-IDF (Term Frequency-Inverse Document Frequency) with practical solved examples to understand document importance scoring. Dive into advanced word embedding techniques including Word2Vec models with both Continuous Bag of Words (CBOW) and Skip-gram architectures for capturing semantic relationships between words. Conclude with Named Entity Recognition (NER) to identify and classify important entities in text such as names, locations, and organizations, providing a solid foundation for building NLP applications and understanding how machines process human language.
