Natural Language Processing (NLP) Full Course | Learn Text Analytics, AI & Python Hands-On - Part 2 скачать в хорошем качестве

Natural Language Processing (NLP) Full Course | Learn Text Analytics, AI & Python Hands-On - Part 2

Welcome to this complete Natural Language Processing (NLP) tutorial — your one-stop guide to understanding how machines read, process, and make sense of human language! In this video, you’ll go from NLP basics to advanced concepts, explore real-world use cases, and build hands-on projects in Python — step-by-step. Whether you’re a beginner, data scientist, or business professional curious about how AI interprets text, this session will equip you with the concepts and confidence to use NLP in real applications. What You’ll Learn: NLP Fundamentals What is NLP and why does it matter? How computers understand text (tokens, corpora, vectorization) Key concepts: Lemmatization, Stopwords, POS tagging NLP vs. traditional Machine Learning Intermediate Concepts Bag of Words (BoW) TF-IDF Vectorization Word Embeddings: Word2Vec, GloVe, FastText Named Entity Recognition (NER) Sentiment Analysis Advanced Topics Topic Modeling: LDA, BERTopic Transformer Models: BERT, RoBERTa, GPT Fine-tuning pre-trained language models Text Summarization & Question Answering Large Language Models (LLMs) and Prompt Engineering Hands-on with Python Text Preprocessing (Tokenization, Cleaning, Lemmatization) Building a Sentiment Analysis Model with Scikit-learn Extracting Entities using SpaCy Using Hugging Face Transformers for real NLP tasks Text Classification and Summarization Real-World Applications (Case Studies) Healthcare: Detect medical terms and patient sentiment from clinical notes. Finance: Identify fraud patterns in transaction text. Customer Support: Auto-tag and prioritize tickets. Marketing: Analyze customer reviews to understand brand perception. Legal & Compliance: Summarize documents and detect risk terms. Technologies & Tools Covered Python NLTK SpaCy Scikit-learn Hugging Face Transformers TensorFlow / PyTorch (for advanced parts) Pandas & Matplotlib for visualization By the End of This Video, You Will: Understand the entire NLP workflow from text to model Be able to preprocess and clean real-world text data Know how to extract meaning, classify, and summarize text Have hands-on experience building NLP pipelines in Python Be ready to apply NLP in your job, research, or projects