Medical Insurance Premium Prediction with Machine Learning

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

Understand the theory and intuition behind artificial neural networks

Build, train and test an artificial neural network model in Keras and Tensorflow

Perform data cleaning, feature engineering and visualization

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 learn how to predict medical insurance cost with machine learning. The objective of this case study is to predict the health insurance cost incurred by Individuals based on their age, gender, Body Mass Index (BMI), number of children, smoking habits, and geo-location. 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

  • Data Science
  • Artificial Neural Network
  • Python Programming
  • Machine Learning

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. Understand the Problem Statement

  2. Import Libraries and Datasets

  3. Perform Exploratory Data Analysis

  4. Practice Opportunity #1 [Optional]

  5. Perform Feature Engineering

  6. Perform Data Visualization

  7. Practice Opportunity #2 [Optional]

  8. Create Training and Testing Datasets

  9. Practice Opportunity #3 [Optional]

  10. Train and Evaluate a Linear Regression Model in Sk-Learn

  11. Train and Evaluate an Artificial Neural Network Regression Model

  12. Practice Opportunity #4 [Optional]

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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