Interactive Word Embeddings using Word2Vec and Plotly

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提供方
Coursera Project Network
在此指导项目中,您将:

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
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

Python ProgrammingMachine LearningNatural Language Processing

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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