Cervical Cancer Risk Prediction Using Machine Learning

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

U​nderstand the theory and intuition behind XGBoost Algorithm

P​reform exploratory data analysis

Develop, train and evaluate XG-Boost classifier model using Scikit-Learn

Clock2 hours
BeginnerPrincipiante
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this hands-on project, we will build and train an XG-Boost classifier to predict whether a person has a risk of having cervical cancer. Cervical cancer kills about 4,000 women in the U.S. and about 300,000 women worldwide. Data has been obtained from 858 patients and include features such as number of pregnancies, smoking habits, Sexually Transmitted Disease (STD), demographics, and historic medical records.

Habilidades que desarrollarás

  • Data Analysis
  • Machine Learning
  • classification
  • Artificial Intelligence(AI)

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Task #1: Understand the Problem Statement and Business Case

  2. Task #2: Import Libraries and Datasets

  3. Task #3: Perform Exploratory Data Analysis

  4. Task #4: Perform Data Visualization

  5. Task #5: Prepare the data before Model Training

  6. Task #6: Understand the Theory and Intuition Behind XG-Boost

  7. Task #7: Train and Evaluate XG-Boost Algorithm

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Preguntas Frecuentes

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