Preparing Data for Machine Learning Models

提供方
Coursera Project Network
在此指导项目中,您将:

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

Clock1.55 hours
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

  • numpy arrays
  • Handling Dataset
  • extracting features
  • Label The Dataset
  • Computer Vision

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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