Preparing Data for Machine Learning Models
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
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.
Skills you will develop
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Setup
Selecting Region of Interest
Features as Numpy arrays
Concatenate the 2 Features Array and Label the Training Dataset.
Final Training Dataset Preprocessing
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In a split-screen video, your instructor guides you step-by-step
Instructor
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