What is Strong AI, and how is it different from the Weak AI?

Strong AI: Strong AI is about creating real intelligence artificially, which means a human-made intelligence that has sentiments, self-awareness, and emotions similar to humans. It is still an assumption that has a concept of building AI agents with thinking, reasoning, and decision-making capabilities similar to humans. Weak AI: Weak AI is the current development stage … Read more

Explain the Hidden Markov model.

Hidden Markov model is a statistical model used for representing the probability distributions over a chain of observations. In the hidden markov model, hidden defines a property that it assumes that the state of a process generated at a particular time is hidden from the observer, and Markov defines that it assumes that the process … Read more

What do you understand by the hyperparameter?

in machine learning, hyperparameter is the parameters that determine and control the complete training process. The examples of these parameters are Learning rate, Hidden Layers, Hidden units, Activation functions, etc. These parameters are external from the model. The selection of good hyperparameters makes a better algorithm. In the context of artificial intelligence and machine learning, … Read more

What are parametric and non-parametric model?

In machine learning, there are mainly two types of models, Parametric and Non-parametric. Here parameters are the predictor variables that are used to build the machine learning model. The explanation of these models is given below: Parametric Model: The parametric models use a fixed number of the parameters to create the ML model. It considers … Read more

What do you understand by the reward maximization?

Reward maximization term is used in reinforcement learning, and which is a goal of the reinforcement learning agent. In RL, a reward is a positive feedback by taking action for a transition from one state to another. If the agent performs a good action by applying optimal policies, he gets a reward, and if he … Read more