Python: Machine Learning with Text Training Course


In this instructor-led, live training, participants will learn how to use the right machine learning and NLP (Natural Language Processing) techniques to extract value from text-based data.

By the end of this training, participants will be able to:

  • Solve text-based data science problems with high-quality, reusable code
  • Apply different aspects of scikit-learn (classification, clustering, regression, dimensionality reduction) to solve problems
  • Build effective machine learning models using text-based data
  • Create a dataset and extract features from unstructured text
  • Visualize data with Matplotlib
  • Build and evaluate models to gain insight
  • Troubleshoot text encoding errors


  • Developers
  • Data Scientists

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice


  • Experience with Python
  • An understanding of machine learning
  • Experience with scikit-learn and pandas

Course Outline


  • The value of text-based data

Workflow for a Text-Based Data Science Problem

Choosing the Right Machine Learning Libraries

Overview of NLP Techniques

Preparing a Dataset

Visualizing the Data

Working with Text Data with scikit-learn

Building a Machine Learning Model

Splitting into Train and Test Sets

Applying Linear Regression and Non-Linear Regression

Applying NLP Techniques

Parsing Text Data Using Regular Expressions

Exploring Other Machine Language Approaches

Troubleshooting Text Encoding Issues

Closing Remarks

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