Give an explanation on the difference between strong AI and weak AI?

Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.

When is it necessary to update an algorithm?

You should update an algorithm when the underlying data source has been changed or whenever there’s a case of non-stationarity. The algorithm should also be updated when you want the model to evolve as data streams through the infrastructure

What are the advantages of neural networks?

Require less formal statistical training
Have the ability to detect nonlinear relationships between variables
Detect all possible interactions between predictor variables
Availability of multiple training algorithms

What is Neural Network in Artificial Intelligence?

In artificial intelligence, neural network is an emulation of a biological neural system, which receives the data, process the data and gives the output based on the algorithm and empirical data.

What are hyperparameters in Deep Neural Networks?

Hyperparameters are variables that define the structure of the network. For example, variables such as the learning rate, define how the network is trained.
They are used to define the number of hidden layers that must be present in a network.
More hidden units can increase the accuracy of the network, whereas a lesser number of units may cause underfitting.

Can you name the properties of a good knowledge representation system?

From the perspective of systems theory, a good knowledge representation system will have the following:

Acquisition efficiency to acquire and incorporate new data
Inferential adequacy to derive knowledge representation structures like symbols when new knowledge is learned from old knowledge
Inferential efficiency to enable the addition of data into existing knowledge structures to help the inference process
Representation adequacy to represent all the knowledge required in a specific domain

For building a Bayes model how many terms are required?

For building a Bayes model in AI, three terms are required; they are one conditional probability and two unconditional probability.

What is Deep Learning?

Deep Learning is a subset of Machine Learning which is used to create an artificial multi-layer neural network. It has self-learning capabilities based on previous instances, and it provides high accuracy.

Name a few Machine Learning algorithms you know.

Logistic regression
Linear regression
Decision trees
Support vector machines
Naive Bayes, and so on

What is a depth-first search algorithm?

Depth-first search (DFS) is based on LIFO (last-in, first-out). A recursion is implemented with LIFO stack data structure. Thus, the nodes are in a different order than in BFS. The path is stored in each iteration from root to leaf nodes in a linear fashion with space requirement.