Topic Modeling using PyCaret

提供方
Coursera Project Network
在此指導 項目中,您將:

build an end-to-end Topic model using PyCaret

Learn how to evaluate a Topic Model

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 1-hour long project-based course, you will create an end-to-end Topic model using PyCaret a low-code Python open-source Machine Learning library. You will learn how to automate the major steps for preprocessing, building, evaluating and deploying Machine Learning Models for Topic . Here are the main steps you will go through: frame the problem, get and prepare the data, discover and visualize the data, create the transformation pipeline, build, evaluate, interpret and deploy the model. This guided project is for seasoned Data Scientists who want to build a accelerate the efficiency in building POC and experiments by using a low-code library. It is also for Citizen data Scientists (professionals working with data) by using the low-code library PyCaret to add machine learning models to the analytics toolkit In order to be successful in this project, you should be familiar with Python and the basic concepts on Machine Learning 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.

您要培養的技能

Topic ModelPython ProgrammingMachine LearningPyCaret

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Introduction and setup environment

  2. Load and Prepare Data

  3. Explore Data

  4. Preprocess Data

  5. Build Topic Model

  6. Evaluate Model

  7. Deploy Model

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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