Question 1

An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

Options :

A : Train the model over multiple desktop computers

B : Train the model on GPUs

C : Use a contractor to do the training portion

D : Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer

Answer: B

Question 2

Your team has built a new robot that roams the halls at your organization and helps with various things such as small deliveries. However, you notice that many employees are opting not to use the robot. When you ask them why they tell you that the robot looks "creepy" and they would rather not interact with it. What's going on here?

Options :

A : Lack of understanding the robot's usefulness

B : The bot is falling into The "Uncanny Valley"

C : Bias towards the robot

D : Safety and reliability issues that impact bot usefulness

Answer: B

Question 3

You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results. What's your best course of action?

Options :

A : Keep going as planned and the problem will eventually correct itself

B : Try to get additional data - at least 5 training examples for each dimension in the representation

C :

Try to get additional information from project lead to see how many examples per dimension are needed

D : Try to improve the quality of your data through more preparation

Answer: B

Question 4

You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique. What is this technique called?

Options :

A : Reinforcement Learning

B : Generative AI

C : Transfer Learning

D : Pre-Trained Models

Answer: C

Question 5

You have been tasked at your organization to manage a large language model (LLM) project. Identify what LLMs are useful for. (Select all that apply.)

Options :

A : Process automation

B : Text summarization

C : Machine Translation

D : Classify and categorize content

E : Code generation

F : Improve search quality

Answer: A,B,C,D,E,F

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