Welcome to Lesson 1 of our course on Natural Language Processing (NLP). Today, we're diving into one of AI's most fascinating and practical fields: Natural Language Processing (NLP), a technology you likely interact with daily through virtual assistants, translation apps, and smart devices.
Welcome to a crucial milestone in your NLP journey - Lesson 2 on Text Preprocessing Techniques. Whether you're building a chatbot, analyzing social media sentiment, or developing a language translation system, the success of your NLP project hinges on how well you prepare your text data.
Welcome to Lesson 3, where we'll explore sentiment analysis – a groundbreaking technology that helps machines understand human emotions in text. Imagine being able to instantly analyze thousands of customer reviews, social media posts, or survey responses to understand exactly how people feel about your product or service.
Welcome to Lesson 4, where we'll unlock the power of Natural Language Processing (NLP) by creating a real-world sentiment analysis model. Ever wondered how companies automatically detect customer satisfaction in thousands of reviews, or how social media platforms track public opinion during major events? Today, you'll learn exactly how this works by building your own sentiment analyzer that can classify text as positive, negative, or neutral.
Welcome to this hands-on NLP (Natural Language Processing) exercise! You’ll build a basic sentiment analysis model that classifies movie reviews as positive or negative. This task is based on the “Sentiment Analysis and Text Classification” lesson and uses Python along with the Natural Language Toolkit (NLTK).
