Question
Question: 1
What is the difference between machine learning and AI?
Machine learning was a concept in early computing, but has since been replaced with the more popular term, artificial intelligence.
Artificial intelligence is a field within Machine learning that focuses on applying learning concepts.
Machine learning is a field within artificial intelligence that focuses on developing algorithms to make computers “intelligent”.
They are interchangeable words and mean the same thing.
Question: 2
What are weights and biases?
Weights are the individual layers in a model and biases are the adjustments made in the layers
Weights are the values applied to each input value and bias is a constant adjustment
Weights are the values applied to each input value and biases are the model inputs
Weights are the model inputs and biases are the values applied to each input value.
Question: 3
If your training data is complex, which would have the most benefit to help fit your model?
Increase the number of nodes in each layer
Increase the number of layers in your model
Increase the number of epochs in your model
Decrease the number of nodes and increase the number of layers
What is the difference between machine learning and AI?
Machine learning was a concept in early computing, but has since been replaced with the more popular term, artificial intelligence.
Artificial intelligence is a field within Machine learning that focuses on applying learning concepts.
Machine learning is a field within artificial intelligence that focuses on developing algorithms to make computers “intelligent”.
They are interchangeable words and mean the same thing.
Question: 2
What are weights and biases?
Weights are the individual layers in a model and biases are the adjustments made in the layers
Weights are the values applied to each input value and bias is a constant adjustment
Weights are the values applied to each input value and biases are the model inputs
Weights are the model inputs and biases are the values applied to each input value.
Question: 3
If your training data is complex, which would have the most benefit to help fit your model?
Increase the number of nodes in each layer
Increase the number of layers in your model
Increase the number of epochs in your model
Decrease the number of nodes and increase the number of layers
Answers
GPT-4o mini
**Question 1: What is the difference between machine learning and AI?**
The correct answer is: **Machine learning is a field within artificial intelligence that focuses on developing algorithms to make computers “intelligent”.**
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**Question 2: What are weights and biases?**
The correct answer is: **Weights are the values applied to each input value and bias is a constant adjustment.**
---
**Question 3: If your training data is complex, which would have the most benefit to help fit your model?**
The correct answer is: **Increase the number of layers in your model.**
(Note: Increasing the number of layers can allow a model to capture more complex patterns in data, which is especially important when dealing with complex training data.)
The correct answer is: **Machine learning is a field within artificial intelligence that focuses on developing algorithms to make computers “intelligent”.**
---
**Question 2: What are weights and biases?**
The correct answer is: **Weights are the values applied to each input value and bias is a constant adjustment.**
---
**Question 3: If your training data is complex, which would have the most benefit to help fit your model?**
The correct answer is: **Increase the number of layers in your model.**
(Note: Increasing the number of layers can allow a model to capture more complex patterns in data, which is especially important when dealing with complex training data.)