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Natural Language Processing (NLP) in Python
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Korshub's take
Comprehensive Text Processing and Analysis in Python
Natural Language Processing (NLP) powers modern text analytics, from search engines to generative models. This intermediate course offers a structured walkthrough of NLP techniques, progressing from classical text normalization to modern transformer architectures.
Who Is This Course For?
Suited for Python developers and data analysts seeking hands-on skills in parsing, vectorizing, and modeling unstructured text data.
Key Takeaways
- Text Normalization: Clean raw text with tokenization, stop-word removal, lemmatization, and stemming.
- Feature Vectorization: Represent text numerically using Bag-of-Words, TF-IDF, and word embeddings like Word2Vec and GloVe.
- Advanced NLP & Transformers: Perform NER, PoS tagging, sentiment classification, and text generation using libraries like NLTK, Scikit-learn, Gensim, and Hugging Face.
About this course
Build a Strong NLP Foundation
Unlock the power of Natural Language Processing (NLP) and take your text analysis skills to the next level! This course equips you with essential tools to process, analyze, and extract insights from text data. Start with the fundamentals of text processing, from tokenization to cleaning and normalizing text by removing stop words, punctuation, and applying lemmatization and stemming to improve text consistency.Extract Meaningful Features from Text
Go beyond raw text and transform it into numerical representations! Explore the Bag-of-Words representation, dive into TF-IDF vectorization, and leverage powerful word embeddings like Word2Vec and GloVe to capture semantic relationships between words.Classify and Generate Text with AI
Harness the power of state-of-the-art transformer models using Hugging Face pipelines. Learn how to perform sentiment analysis, classify content, analyze question-answer relationships, assess grammatical acceptability, and generate text using various models. Explore Named Entity Recognition (NER), Part-of-Speech (PoS) tagging, text summarization, and translation to expand your NLP toolkit.Master key NLP libraries
By the end of this course, you’ll have a strong grasp of NLP fundamentals and hands-on experience with key libraries such as nltk, sklearn, gensim, and Hugging Face’s transformers. Start your journey today and transform the way you interact with text data!Advertisement