ML: Diagnose the presence of Breast Cancer with Python

提供:
Coursera Project Network
このガイド付きプロジェクトでは、次のことを行います。

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
Intermediate中級
Cloudダウンロード不要
Video分割画面ビデオ
Comment Dots英語
Laptopデスクトップのみ

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.

あなたが開発するスキル

  • Machine Learning
  • Python Programming
  • Jupyter Notebook
  • Data Visualization (DataViz)
  • Supervised Learning

ステップバイステップで学習します

ワークエリアを使用した分割画面で再生するビデオでは、講師がこれらの手順を説明します。

  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.

ガイド付きプロジェクトの仕組み

ワークスペースは、ブラウザに完全にロードされたクラウドデスクトップですので、ダウンロードは不要です

分割画面のビデオで、講師が手順ごとにガイドします

よくある質問

よくある質問

さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。