Preparing Data for Machine Learning Models
Offered By: Coursera Project Network via Coursera
Course Description
Overview
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.
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.
Syllabus
- Project Overview
- In this project, you will be able to extract features as pixels color from Image, and handle it in numpy arrays, you will process those arrays and annotate the dataset.
Taught by
Yara Yasser
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