Medical Insurance Premium Prediction with Machine Learning

제공자:
Coursera Project Network
학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

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
Beginner초급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

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.

개발할 기술

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

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  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]

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

자주 묻는 질문

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