This hands-on course introduces Natural Language Processing (NLP) through real-world machine learning applications built with Flask. You'll learn how to clean and structure text using RegEx and lemmatization, perform sentiment analysis with Naive Bayes, TextBlob, and VADER, and develop a movie recommendation system using TF-IDF and cosine similarity.
The course also covers Flask fundamentals, dynamic HTML templating, and API integration for working with live data. By the end, you'll deploy a complete Movie Recommender App, gaining practical experience in applied machine learning and web application development.
What You Will Learn
- Build a complete NLP pipeline, including cleaning with RegEx, removing stopwords, lemmatizing, and vectorizing text.
- Train and evaluate a Naive Bayes machine learning model to classify movie reviews as positive or negative.
- Compare and apply pre-trained sentiment scoring systems such as TextBlob and VADER.
- Develop a recommendation engine that suggests similar products through NLP techniques.
- Learn Flask fundamentals by building search apps, integrating APIs, and serving ML models in the browser.
- Complete a capstone project by creating a Flask-powered Movie Recommender App that brings together NLP, machine learning, and web development.
This course is available for 30 days. You can choose when to start your access period. Once you activate, you will have 30 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable.
