Advantages And Disadvantages Of Machine Learning System

Artificial intelligence can be defined as the ability of a computer performing activities normally considered to require human intelligence. According to Blay Whitby, “Artificial Intelligence (AI) is the study of intelligent behavior (in humans, animals, and machines) and the attempt to find ways in which such behavior could be engineered in any type of artifact. It is one of the most difficult and arguably the most exciting enterprise ever undertaken by humanity” (1). Technology is moving at a fast speed, and today we have more advantages than ever before. The amazing power we have now all because of artificial intelligence (AI) is crazy. AI is located far and wide nowadays. It would be difficult for a person to go their whole lifetime

Artificial intelligence is a part of computer science that produces machines that can do some of same things humans do. There are computers that have been designed to recognize speech, solve problems, make plans, and learn different functions. The concerns of the panel of experts

Data mining is a class of database applications that looks for hidden patterns in a group of data that can be

Artificial intelligence is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. All artificial intelligence can be put in three different bands, Artificial Narrow Intelligence, where a machine is programed to have a particular expertise, Artificial General Intelligence where a machine’s

The authors say that the growth and development of artificial intelligence need to teach machines to learn from themselves. The authors support the idea by introducing two distinct groups and their ideas about machine learning. For instance, one of these groups believes that making manual corrections to algorithms is necessary. This means when a machine does not make a right decision, making manual corrections helps it to learn what the right decision is. This article was recently published in a popular American quarterly magazine. It is somewhat relevant to the topic, and its objectivity is neutral, but there is nothing about the qualifications of the authors on the web. It seems they may not be educated in computer

4) Technically speaking, data mining is a process that uses statistical, mathematical, and artificial intelligence techniques to extract and identify useful information and

The concept of artificial intelligence was first labeled by a man named Alan Turing in 1950, he believed that the future would hold the possibility for man to communicate with computers and sustain a conversation (Atkinson, Solar 1). Although, we have reached the point where it is possible to hold a simple preprogrammed conversation with a computer and give them the ability to learn, there is still a long way to go in making computers fully artificially intelligent. Atkinson and Solar continue to describe some real world applications of artificial intelligence such as, “Data mining technologies, fraud detection, and industrial-strength optimization” (8). In these examples, forms of artificial intelligence like cognitive reasoning abilities are already being used making the demand for them higher.

Artificial intelligence, or AI, is a field of computer science that attempts to simulate characteristics of human intelligence or senses. These include learning, reasoning, and adapting. This field studies the designs of intelligent

Data mining simply explained is automated sorting and analyzing of large amounts of data, searching for patterns and correlations. On a

Data Mining is a computer based-process for converting large data volumes to information and knowledge by finding patterns within the data using different techniques. It is sorting through data to identify patterns and establish relationships. Data mining helps resolving problems that are time consuming when traditional techniques are used. Data mining techniques are used to predict future trends and to make wise decisions. There are multiple Data Mining techniques available to the Data diggers to make their life easy. In my study report I will be discussing about the different mining techniques, advantages and disadvantages and also about a use case of the data mining techniques on shark attack dataset to predict the attack of sharks based on various attributes.

The overall goal of the data mining process is to extract information from data sets and transform it into an understandable structure such as patterns and knowledge for further use [3].

Many other terms are being used to interpret data mining, such as knowledge mining from databases, knowledge extraction, data analysis, and data archaeology. Data mining is one of the provoking and significant areas of research. Data mining is implicit and non-trivial task of identifying the viable, novel, inherently efficient and perspicuous patterns of data. Figure 1 represents the data mining as part of KDD process. The hidden relationships and trends are not precisely distinct from reviewing the data. Data mining is a multi-level process involves extracting the data by retrieving and assembling them, data mining algorithms, evaluate the results and capture them. Data Mining is also revealed as necessary process where bright methods are used to extract the data patterns by passing through miscellaneous data mining

The system suffers from complication in use at lower levels, which requires extensive training and significant leap in the learning curve before all features can be utilized fully.

The Data mining have many techniques for extracting dataset like Clustering, Classification, Regression, and Association Rule Learning. The clustering technique is the task of discovering structures in homogeneous data to be in one group, there the

Data mining generally is the process of analysing data from different perspectives and summarising it into useful information (Thuraisingham, 1999). It is also called the “Knowledge Discovery in Databases” process. It can be understand in the way of discovering interesting and useful patterns and relationships in large volumes of data. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for future use. (Han & Kamber, 2006)