Preparing Data for Machine Learning Models

提供方
Coursera Project Network
在此免費的指導 項目中,您將:

Be Able to Select a Region of Interest and Extract Features from it, so it will be your Training Dataset.

Get Introduced to Several Numpy Functions

Label the Training Dataset

在面試中展現此實踐經驗

Clock1.55 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

By the end of this project, you will extract colors pixels as training dataset into a form where you can feed it to your Machine Learning Model using numpy arrays. In this project we will work with images, you will get introduced to computer vision basic concepts. Moreover, you will be able to properly handle arrays and preprocess your training dataset and label it. Extracting features and preparing data is a very crucial task as it influences your model. So you will start to learn the basics of handling the data into the format where it would be accepted by a Machine Learning algorithm as Training Dataset.

必備條件

Basic Knowledge of Python

Basic Knowledge of Machine Learning

您要培養的技能

numpy arraysHandling Datasetextracting featuresLabel The DatasetComputer Vision

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. Introduction and Setup

  2. Selecting Region of Interest

  3. Features as Numpy arrays

  4. Concatenate the 2 Features Array and Label the Training Dataset.

  5. Final Training Dataset Preprocessing

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

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常見問題

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