Machine Learning Model Training Guide

This video tutorial guides viewers through creating a machine learning model for dog breed identification without coding. It covers downloading images, creating datasets, using Teachable Machine, and testing the model. The tutorial emphasizes ease of use and provides a link to Teachable Machine. The video concludes with a promise of more detailed tutorials in the future.

What is the main objective of the tutorial video?

• To explore different dog breeds

• To understand the history of machine learning

• To build a dog breed identification model without coding

• To learn coding for machine learning

How many images per dog breed are recommended for downloading?

• At least 15 images

• At least 10 images

• At least 5 images

• At least 20 images

What percentage of images should be used for testing data?

• 10%

• 20%

• 30%

• 40%

Which platform is used to create the machine learning model in this tutorial?

• TensorFlow

• PyTorch

• Teachable Machine

• Scikit-learn

What is the first step after accessing the Teachable Machine site?

• Download more images

• Train the model

• Upload test data

• Click the 'Get Started' button

What is the purpose of the video description link?

• To subscribe to the channel

• To view the video transcript

• To access the Teachable Machine site

• To download more images

What should you do if you have more than two dog breeds?

• Add another class in the model

• Delete some images

• Use only two breeds

• Ignore the extra breeds

What is the next step after uploading the training data?

• Download more images

• Train the model

• Test the model

• Change the class names

What is the accuracy of the trained model as shown in the video?

• 80%

• 90%

• 95%

• 100%

What type of machine learning is used in this tutorial?

• Semi-supervised learning

• Reinforcement learning

• Unsupervised learning

• Supervised learning