No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Validating Accuracy of Batch Predictions

The video tutorial discusses comparing predicted and actual data results, achieving a 99.2% accuracy using Excel. It highlights the use of Amazon SageMaker Canvas in a banknote authentication project, explaining the process of using training data to build a model and manage its accuracy. The tutorial concludes with a brief mention of future projects and appreciation for the technology.

What was the accuracy rate achieved in the comparison of predicted and actual data?

• 95.5%

• 99.2%

• 97.5%

• 98.0%

How many cases out of 631 had mismatched predictions?

• 20

• 5

• 10

• 15

What tool was used for the banknote authentication project?

• IBM Watson

• Microsoft Azure ML

• Google Cloud AI

• Amazon SageMaker Canvas

What can be adjusted to manage the model's accuracy?

• Training data size

• Type of algorithm

• Number of predictions

• Selection of columns

What is the speaker's attitude towards learning new technology?

• Confused

• Indifferent

• Excited

• Worried