Perform Sentiment Analysis with scikit-learn
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
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
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Importing the Data
Transforming Documents into Feature Vectors
Term Frequency-Inverse Document Frequency
Calculate TF-IDF of the Term 'Is'
Data Preparation
Tokenization of Documents
Document Classification Using Logistic Regression
Load Saved Model from Disk
Model Accuracy
How Guided Projects work
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
Reviews
TOP REVIEWS FROM PERFORM SENTIMENT ANALYSIS WITH SCIKIT-LEARN
This project is very useful for people that don't know anything about sentiment analysis and it's approach with Scikitlearn, like me. It's very introductory.
Very well designed course. Starting from the beginning of text pre-processing till evaluation of model, all steps are explained and implemented very well.
I love the part that you had to write your codes as the teacher was teaching. It was a great introduction for me to text and sentiment analysis
Guided Project should be longer may be of 3-4 hours and consists of real world industry problem. It would be beneficial fo bachelors students.
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