Build NLP pipelines using scikit-learn

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In this Guided Project, you will:

Understand the business problem and the dataset and generate hypothesis to create new features based on existing data

Perform text pre-processing and creating custom transformers to generate new features in to pass into the machine learning pipeline

Implement NLP pipeline and build a text classification model

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

In this 2-hour long project-based course, you will understand the business problem and the dataset and learn how to generate a hypothesis to create new features based on existing data. You will learn to perform text pre-processing and creating custom transformers to generate new features in to pass into the machine learning pipeline. And you will implement NLP pipeline creating your own custom transformers and build a text classification model. 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.

Skills you will develop

Natural Language ProcessingCustom TransformersFeature UnionText CleaningMachine Leaning Pipeline

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:

  1. Understand and loading the dataset

  2. Text preprocessing

  3. Exploratory Data Analysis

  4. Create custom transformers

  5. Model Building using FeatureUnion

  6. Model Evaluation

  7. Conclusion and next steps

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

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.