ML: Diagnose the presence of Breast Cancer with Python

oferecido por
Coursera Project Network
Neste Projeto Guiado, você irá:

Learn how to set up a Jupyter notebook, load data and convert it to data frame.

Preview and visualize loaded data.

Train, test and evaluate a machine learning model.

Clock1 hour
IntermediateIntermediário
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

In this 1-hour long project-based course, you will learn how to set up and run your Jupyter Notebook, load, preview and visualize data, then train, test and evaluate a machine learning model that predicts if a patient has breast cancer or not. 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.

Habilidades que você desenvolverá

Machine LearningPython ProgrammingJupyter NotebookData Visualization (DataViz)Supervised Learning

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. By the end of Task 1, you will get an overview of this guided project, Jupyter notebooks which will be used and how you will have set up your notebook environment for this project.

  2. By the end of Task 2, you will have begun the process of building the project template by first loading the data, previewing and exploring it.

  3. By the end of Task 3, you will have checked for missing values, explored data types and visualized features in the data using seaborn.

  4. By the end of Task 4, you will have trained different classifier models, run predictions with them and evaluate their various performances using accuracy score.

  5. By the end of Task 5, you will have combined your predictions with test features and saved your outputs in CSV file format.

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.