Interviews are tough. Even for the most competent candidates.
Research says the candidate must demonstrate high-energy and confidence. Because whatever you say during the interview will impact the hiring manager, even though you get the job or not.
Even for an AI career, some of the interview questions tend to come up time and again. So, what is the best way to deal with them? Let us have a look at some of the most frequently asked AI interview questions and see how to answer them.
Question 1. Define Artificial Intelligence (AI)?
Answer: Artificial Intelligence comes under the branch of science that deals with developing intelligent machines that can think, work, and react the way humans do.
Question 2. Can you mention the sectors with the greatest impact on AI?
Answer: In the present day, AI has almost paved its pathway into numerous fields, to name a few would be –
- Bioinformatics
- Computing field
- Humanoid robots
- Weather forecasting
- Speech Recognition
- Space and Aeronautics
Answer: Both Overfitting and Underfitting hold accountable for poor performance. For instance, Overfitting tends to provide good performance on any trained data but poorer generalization to the other data. Whereas, Underfitting provides good performance on the training data alongside good generalization to the other data as well.
Question 4. What are the preferred programming languages for AI an AI engineer must know?
Answer: Well, if you’ve chosen this field, you need to be well-equipped with languages such as Python, R, Java, Prolog, and Lisp. These are some of the most common programming languages preferred in the AI field.
Question 5. What’s your awareness scale in terms of using AI-enabled services or devices?
Answer: AI is omnipresent and has drastically impacted the way we live and work. We can see AI in a lot of things today, some of which are –
- Social Media Feeds
- Smartphones
- Video games
- Media players
- Smart Cars and Drones, etc.
Answer: Tree topology can have several connected element arrangements just as the branches of the tree. Such type of structure ideally has three specific levels that are accessible and scalable, however, troubleshooting will also be preferred.
However, there’s one drawback to the topology, there are chances of malfunction of the primary node.
Question 7. What’s the formula for coefficient – logistic regression?
Answer: The logistic regression can be defined by –
πi=Pr(Yi=1|Xi=xi)=exp(β0+β1xi)1+exp(β0+β1xi)
Moving ahead, the questions asked to an aspiring AI engineer can get a little challenging from here onwards. The hiring manager might hop on to asking more AI advanced questions. You just need to be prepared.
Question 8. Can you make a list of the most commonly used techniques in AI?
Answer: You will find some of the most-used algorithms in AI. Some of the first algorithms introduced solving complex problems include names like –
- Generic Algorithms
- Reinforcement Learning
- Neural Network
Answer: Below is the list of the used AI software platforms –
- Ayasdi
- Salesforce Einstein
- Tensor Flow
- Cloud Machine Learning
- Azure Machine Learning
- Playment
Answer: This question is one of the most asked interview questions when you’re seeking an AI career. You need to make sure you answer it correctly.
Well, searching is one technique that is a universal technique often used in the AI problem technique. The algorithm used here is to search a particular position and every specific terminology has a different component. For instance –
- Problem Space Graph – used for representing a problem state
- Problem space – an environment where the actual problem happens
- Space Complexity – this is calculated with the maximum number of nodes already formed
- Problem Instance – this is the result of the initial state and goal state
- The depth of a problem – the length of the shortest path can be determined
- Depth – this defines the length of the shortest path – from inception to the goal state
- Time Complexity – this is where the maximum number of nodes created can be defined
- Branching Factors – the calculation is easily made by defining the average number of child nodes found in the problem space graph
- Admissibility – this helps find optimal solutions
- Bidirectional search
- Breadth-first search
- Uniform cost search
- Depth-first search
Answer: You can find two best hyperparameters in a tree-based model, and they are –
- Measuring the performance over the validation data
- Measuring the performance over the training data
Preparing for an AI interview can be stressful. However, with the help of the given questions, you shouldn’t’ have any problems preparing yourself for the interview.