Machine Learning: 2 Books in 1: Machine Learning for Beginners, Machine Learning Mathematics. An Introduction Guide to Understand Data Science Through the Business Application

Knowledge – For machines to be able to act and react like humans, they
require an abundance of data and information of the world around us. To be
able to implement knowledge engineering AI must have seamless access to
data objects, data categories, and data properties as well as the relationship
between them that can be managed and stored in the data storages. 

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Learning – Of all the different forms of learning applicable to AI, the
simplest one is “trial and error” method. For example, a chess learning
computer program will try all possible moves until the mate-in-one move is
found to end the game. This move is then stored by the program to be used
the next time it encounters the same position. This relatively easy-to-
implement aspect of learning called “rote learning” involves simple
memorization of individual items and procedures. The most challenging
part of the learning is called “generalization”, which involves applying the
past experience to the corresponding new scenarios.
Problem Solving – The systematic process to reach a predefined goal or
solution by searching through a range of possible actions can be defined as
problem-solving. The problem-solving techniques can be customized for a
particular problem or used for a wide variety of problems. A general-
purpose problem-solving method frequently used in AI is "means-end
analysis", which involves a step-by-step deduction of the difference
between the current state and final state of the goal. Think about some of
the basic functions of a robot, back and forth movement, or picking up stuff
that leads to the fulfillment of a goal. 
Reasoning – The act of reasoning can be defined as the ability to draw
inferences that are appropriate to the given situation. The two forms of
reasoning are called “deductive reasoning” and “inductive reasoning”.
According to “deductive reasoning”, if the premise is true then the
conclusion is assumed to be true. On the other hand, in the “inductive
reasoning”, even if the premise is true, the conclusion may or may not be
true. Although considerable success has been achieved in programming
computers to perform deductive reasoning, the implementation of “true

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reasoning” remains aloof and one of the biggest challenge facing Artificial
Intelligence.
Perception – The process of generating a multidimensional view of an
object using various sensory organs can be defined as perception. This
creation of awareness of the environment is complicated by several factors,
such as the viewing angle, the direction, and intensity of the light and the
amount of contrast produced by the object, with the surrounding field.
Breakthrough developments have been made in the field of artificial
perception and can be easily observed in our daily life with the advent of
self-driving cars and robots that can collect empty soda cans while moving
through the buildings.