Tuesday, April 13, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Neural Networks

How To Describe a Dataset For A Computer Vision Classification Problem | by Samer Sallam | Nov, 2020

November 18, 2020
in Neural Networks
How To Describe a Dataset For A Computer Vision Classification Problem | by Samer Sallam | Nov, 2020
587
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

As a data scientist I worked on several machine learning and deep learning projects related to the computer vision field. In each project, I was asking myself how to choose the best dataset, and I realized that an accurate and well-organized description would give me the right answer. In this article, I would like to share with you the following table (table 1) which I developed to describe a dataset of images for classification projects in machine learning.

  • General information: Dataset name, link, and size.
  • Images dimensions: Dimension range for both width and height gives you a better idea about the images and about the transformation that you may apply, also an average value gives you an intuition about the dimension value for most images.
  • Number of images: · Depending on the problem you want to solve, there will be an acceptable number that you can deal with. But if the problem is very complex, then this number may need to be sufficient to cover all the possible cases.
  • Number of classes: The number of classes will help you choose and set up a ML/DL algorithm.
  • Number of images per class: It is very important to know whether the dataset is balanced or imbalanced as it will affect the whole process of training and validating of the ML/DL model.
  • Number of images per extension: Sometimes we are interested in a specific image extension. This info will help you to know the portion of images per extension
  • Images File size: Will give you an intuition about the images file size distribution.
  • Notes: This is useful if you want to add some additional information or notes about the dataset. (such as permissions, ethics…etc)
Artificial Intelligence Jobs

1. How to automatically deskew (straighten) a text image using OpenCV

You might also like

Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021

BERT Transformers — How Do They Work? | by James Montantes | Apr, 2021

Learning Not To Fear Machine Learning | by Dimitry Belozersky | Apr, 2021

2. Explanation of YOLO V4 a one stage detector

3. 5 Best Artificial Intelligence Online Courses for Beginners in 2020

4. A Non Mathematical guide to the mathematics behind Machine Learning

In order to understand the idea better let me show you a quick demo. The following table (Table 2) shows a description of a Covid19 dataset from Kaggle website.

This is all for this article, I hope you find it useful, and would you please share with me your ideas about the discussed topic.

Credit: BecomingHuman By: Samer Sallam

Previous Post

Programmatic Advertising's ROI Dilemma | Marketing Study

Next Post

Machine learning automation startup DataRobot raises $270M ahead of likely IPO

Related Posts

Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021
Neural Networks

Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021

April 13, 2021
BERT Transformers — How Do They Work? | by James Montantes | Apr, 2021
Neural Networks

BERT Transformers — How Do They Work? | by James Montantes | Apr, 2021

April 13, 2021
Learning Not To Fear Machine Learning | by Dimitry Belozersky | Apr, 2021
Neural Networks

Learning Not To Fear Machine Learning | by Dimitry Belozersky | Apr, 2021

April 13, 2021
WOMEN IN A.I. ~ Future is Female
Neural Networks

WOMEN IN A.I. ~ Future is Female

April 12, 2021
A Primer of 29 Interactions for AI
Neural Networks

A Primer of 29 Interactions for AI

April 10, 2021
Next Post
Machine learning automation startup DataRobot raises $270M ahead of likely IPO

Machine learning automation startup DataRobot raises $270M ahead of likely IPO

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

AI.Reverie Appoints Former NVIDIA Deep Learning Guru Aayush Prakash as Head of Machine Learning
Machine Learning

AI.Reverie Appoints Former NVIDIA Deep Learning Guru Aayush Prakash as Head of Machine Learning

April 13, 2021
Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021
Neural Networks

Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021

April 13, 2021
The rise of headless and hybrid CMS: Tuesday’s daily brief
Digital Marketing

The rise of headless and hybrid CMS: Tuesday’s daily brief

April 13, 2021
Brave browser disables Google’s FLoC tracking system
Internet Security

Brave browser disables Google’s FLoC tracking system

April 13, 2021
New NAME:WRECK Vulnerabilities Impact Nearly 100 Million IoT Devices
Internet Privacy

New NAME:WRECK Vulnerabilities Impact Nearly 100 Million IoT Devices

April 13, 2021
Machine Learning Approach In Fantasy Sports: Cricket
Machine Learning

Machine Learning Approach In Fantasy Sports: Cricket

April 13, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • AI.Reverie Appoints Former NVIDIA Deep Learning Guru Aayush Prakash as Head of Machine Learning April 13, 2021
  • Music and Artificial Intelligence | by Ryan M. Raiker, MBA | Apr, 2021 April 13, 2021
  • The rise of headless and hybrid CMS: Tuesday’s daily brief April 13, 2021
  • Brave browser disables Google’s FLoC tracking system April 13, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates