Perform Sentiment Analysis with scikit-learn

4.4
stars
105 ratings
17 reviews
Offered By
Rhyme
In this Guided Project, you will:

Build and employ a logistic regression classifier using scikit-learn

Clean and pre-process text data

Perform feature extraction with The Natural Language Toolkit (NLTK)

Tune model hyperparameters and evaluate model accuracy

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this project-based course, you will learn the fundamentals of sentiment analysis, and build a logistic regression model to classify movie reviews as either positive or negative. We will use the popular IMDB data set. Our goal is to use a simple logistic regression estimator from scikit-learn for document classification. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Data ScienceMachine LearningPython ProgrammingData AnalysisScikit-Learn

Learn step-by-step

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    Your workspace is a cloud desktop right in your browser, no download required

    In a split-screen video, your instructor guides you step-by-step

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