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1. Is multi-class classification possible using neural networks? Choose the best answer.
2. You want to build a machine learning model that will perform image recognition What type of approach would be best suited for this scenario?
3. Which is not a logic gate?
4. You notice that your data has a mix of Imperial and Metric measures for a key data component. What type of data preparation might you use?
5. One of your colleagues is proposing the use of regression in a supervised model to evaluate whether we should mail a catalog to certain customers. What is your opinion of this proposal?
6. Which of the following are accurate about the Dartmouth Summer Research Project in 1956? (Choose 2)
7. What is the main goal of machine learning models?
8. Which best describes a major limitation on single-layer neural networks?
9. Which of the following is a characteristic of an algorithm? (Choose 3)
10. Which of the following characteristics best represents a major leap forward for computers in the 1940's? (Choose 2)
11. In reinforcement learning, what is the name for the set of instructions that is created during the training process and ultimately is used to make decisions?
12. You want to build a machine learning model that will translate speech to text. What type of approach would be best suited for this scenario?
13. Which is the closest to the definition of entropy?
14. You notice that your model performs great in the training process but really bad in the testing phase. What might be a cause of this? (Choose 2)
15. If you want to store digitized documents in a database, what data type would you most likely use?
16. What ML concept best describes a collection of data you know to be accurate and a good starting point for Supervised model training?
17. What is the simplest style of neural network?
18. What is the main difference between supervised and unsupervised learning?
You want to create a machine learning model that will flag e-commerce transactions as potentially fraudulent as they happen based on correlation between multiple factors. What type of machine learning model are you most likely to build?

20. You want to create a circuit that will turn on a light when two separate buttons are pressed. What is the single logic gate you could use to create this circuit?
21. Which aspect of neural network training can we use to influence the threshold of when a neuron gets activated?
22. What is the process of going back through the layers of a neural network and adjusting weights to improve the results during training?
23. You notice your dataset has certain values misspelled. What type of data preparation might you use?
24. What is one thing you might do to ensure that the data will be well distributed among the training, testing and validation sets?
25. You are defining a dataset to be used in training a machine learning model that will forecast sales for next week based on this last week's sales. What is the most common way to divide up the past 10 years of data into the training and testing datasets (assuming no validation set is required)?


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