Interactive Word Embeddings using Word2Vec and Plotly

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In this Guided Project, you will:

Clean and preprocess text data for modeling

Train and evaluate word embedding models

Build an interactive network graph that can be used for recommendations and related item discovery

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

In this 2 hour long project, you will learn how to preprocess a text dataset comprising recipes. You will learn how to use natural language processing techniques to generate word embeddings for these ingredients, using Word2Vec. These word embeddings can be used for recommendations in an online store based on added items in a basket, or to suggest alternative items as replacements when stock is limited. You will build this recommendation/discovery feature in an interactive and aesthetic visualization tool. 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

Python ProgrammingMachine LearningNatural Language Processing

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. Introduction to the task and demo

  2. Exploratory data analysis and preprocessing

  3. Model theory and training

  4. Basic model results analysis

  5. Building interactive visual tool with graphs for full-scale analysis

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.