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.
Interactive Word Embeddings using Word2Vec and Plotly
Instructor: Ari Anastassiou
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What you'll learn
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
Skills you'll practice
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Guided Project
Recommended experience
(42 reviews)
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About this Guided Project
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:
Introduction to the task and demo
Exploratory data analysis and preprocessing
Model theory and training
Basic model results analysis
Building interactive visual tool with graphs for full-scale analysis
Recommended experience
Intermediate Python users with some experience with Natural Language Processing and/or Machine Learning.
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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