Part of Speech Tagging

Introduction

In this notebook, you'll use the Pomegranate library to build a hidden Markov model for part of speech tagging with a universal tagset . Hidden Markov models have been able to achieve >96% tag accuracy with larger tagsets on realistic text corpora. Hidden Markov models have also been used for speech recognition and speech generation, machine translation, gene recognition for bioinformatics, and human gesture recognition for computer vision, and more.

The notebook already contains some code to get you started. You only need to add some new functionality in the areas indicated to complete the project; you will not need to modify the included code beyond what is requested. Sections that begin with 'IMPLEMENTATION' in the header indicate that you must provide code in the block that follows. Instructions will be provided for each section, and the specifics of the implementation are marked in the code block with a 'TODO' statement. Please be sure to read the instructions carefully!

Evaluation

Your project will be reviewed by a Udacity reviewer against the project rubric here . Review this rubric thoroughly, and self-evaluate your project before submission. All criteria found in the rubric must meet specifications for you to pass.

Submission

Once you have completed all of the code implementations, you need to finalize your work by exporting the iPython Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You must then export the notebook by running the last cell in the notebook, or by using the menu above and navigating to File -> Download as -> HTML (.html) Your submissions should include both the html and ipynb files.

Add the "hmm tagger.ipynb" and "hmm tagger.html" files to a zip archive and submit it with the button below. ( NOTE: If you complete the project in the workspace, then you can submit directly using the "submit" button in the workspace.)

Project Submission Checklist

Before submitting your project, please review and confirm the following items.
I am confident all rubric items have been met and my project will pass as submitted.
Project builds correctly without errors and runs.
All required functionality exists and my project behaves as expected per the project's specifications.

Once you have checked all these items, you are ready to submit!