Time Machine Week 14

How do humans acquire new knowledge and behaviors?

• By avoiding experiences

• Through formal education only

• Through experiences, observations, and guidance

• By relying solely on intuition

What is the focus of Machine Learning?

• Manual data entry.

• Building systems to predict and decide based on learned data.

• Creating complex algorithms.

• Building hardware components.

What do we do after collecting and analyzing information

• Ignore the information

• Make decisions and convey emotions

• Repeat the process

• Stop analyzing

What types of information can be collected for Machine Learning?

• Only pictures and words

• Only numbers and facts

• Anything from pictures and words to numbers and facts

• Only text-based information

Put the following steps in the machine learning process in the correct sequence

• Data collection, Model Training, Model Test, Deployment

• Data collection,Model Test, Deployment, Model Training

• Data collection, Model Test, Model Training, Deployment

• Deployment,Data collection, Model Test, Model Training

Which of the following statements about Teachable Machine is true

• It requires advanced programming skills to use.

• It simplifies the process of creating custom models without complex coding.

• It is only available as a desktop application.

• It is developed by Microsoft.

What is the role of the "Model" in Machine Learning?

• Providing data

• Analyzing data

• Training the machine

• Taking actions

How does the Machine Learning Model improve its ability to make predictions?

• By ignoring new data

• By repeating the same actions

• By learning from new data

• By avoiding data analysis

What type of information does the "Outputs" stage provide in Machine Learning?

• Training data

• Analytical algorithms

• Unrelated data   

• Results based on learning

What is the significance of the deployment step in the Machine Learning process?

• It marks the end of the Machine Learning process

• It allows the model to be utilized and make predictions on new data

• It involves retraining the model with updated data

• It is an optional step and not essential for a functioning model