Understand python programming fundamentals for Natural Language Processing
Create a pipeline to remove stop-words, perform tokenization and padding
Train and test Naive Bayes Classifier Models
In this hands-on project, we will predict customer sentiment using natural language processing techniques. In this project, we will build a machine learning model to analyze thousands of amazon echo reviews to predict customers sentiment. Artificial Intelligence and Machine Learning (AI/ML)-based sentiment analysis is crucial for companies to automatically predict whether their customers are happy or not. This project is practical and directly applicable to any company with that has online presence. The algorithm could be used automatically detect customers sentiment. Note: 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.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Understand the Problem Statement and Business Case
Import Libraries and Datasets
Perform Data Visualization
Perform Data Exploration
Plot the wordcloud
Text Data Cleaning 101
Perform Count Vectorization (Tokenization)
Create a Complete Text Processing Pipeline
Train and Test a Naive Bayes Classifier Model
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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You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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