Preparing Data for Machine Learning Models

ofrecido por
Coursera Project Network
En este Proyecto guiado, tú:

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
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

numpy arraysHandling Datasetextracting featuresLabel The DatasetComputer Vision

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

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