Python Machine Learning Advanced (Self-Paced)
Self-paced: Build NLP workflows, sentiment analysis models, and a movie recommendation app with Flask.
Self-paced: Build NLP workflows, sentiment analysis models, and a movie recommendation app with Flask.
This is the self-paced course. For live instruction, enroll in Python Machine Learning Advanced.
In this self-paced course, apply machine learning to text and build a Flask web application. Clean text with regular expressions and lemmatization, train a Naive Bayes sentiment model, and compare results with TextBlob and VADER.
Use TF-IDF and cosine similarity to create a recommendation system. Practice Flask fundamentals, dynamic HTML templates, and API integration, then combine the work in a Movie Recommender App.
Learn the concepts and skills covered in this course or your tuition is on us. See details and terms & conditions.
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Yes, this course is open to beginners. Students must be comfortable using a computer. No other prior knowledge is required.
This course does not qualify for payment plans or student financing. See our Payment Plan FAQ to find related programs that qualify.
For this course, you are entitled to a 90% refund (your payment less the nonrefundable 10% registration fee) within 30 days of purchase if you have not accessed the course materials.
There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us.
However, you may need to obtain required software. We’ll help you get set up with a free trial of paid software prior to the class. Most of our coding classes utilize freely-available open-source software. For most of our design and motion graphics courses, we will help you get set up with a free trial of Adobe Creative Cloud. If you attend the course in-person, we will have a computer already set up for you with all of the required software for no additional cost.
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Start coding in Python by mastering fundamental programming concepts and syntax from scratch. You'll learn to work with data types, control flow, functions, and object-oriented principles, establishing a solid foundation for building structured programs.
Beginners in Python and pandas should complete the Python Data Science & Machine Learning Bootcamp first. This advanced self-paced course expects those foundations already and centers on NLP and deploying models with Flask.
Build Python machine learning models, prepare data, select features, and evaluate predictions using regression, classification, and tree-based methods.
Regression, classification, and scikit-learn fundamentals come from Python Machine Learning Bootcamp, which belongs earlier in the sequence. This advanced self-paced course extends them into NLP and a Flask-powered recommender app.
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