Annotated Bibliography On Machine Learning

Data mining has popular technology for extracting interesting information for multimedia data sets, such as audio, video, images, graphics, speech, text and combination of several types of data set. Multimedia data are unstructured data or semi-structured data. These data are stored in multimedia database, multimedia mining which is used to find information from large multimedia database system, using multimedia techniques and powerful tools. The current approaches and techniques are explained for mining multimedia data. This paper analyzes about the use of essential characteristics of multimedia data mining, retrieving information is one of the goals of data mining and different issues have been discussed.

When someone brings up the term “artificial intelligence”, a variety of connotations tend to arise, connotations that often are unfair or unrepresentative of the true real-world applications of such a term. Due to the incidentally fear-mongering nature of the media, artificial intelligence can refer to something as basic as a robotic arm in a factory, as well as the implied extinction and/or enslavement of the human race as caused by robo-revolution. As of today, however, when applied in the world of modern technology, artificial intelligence is defined as any innovation that performs a task usually completed by humans. Of course, with this definition, artificial intelligence holds the potential for both societal harm and benefit, and its fate

One of the hottest topics that modern science has been focusing on for a long time is the field of artificial intelligence, the study of intelligence in machines or, according to Minsky, “the science of making machines do things that would require intelligence if done by men”.(qtd in Copeland 1). Artificial Intelligence has a lot of applications and is used in many areas. “We often don’t notice it but AI is all around us. It is present in computer games, in the cruise control in our cars and the servers that route our email.” (BBC 1). Different goals have been set for the science of Artificial Intelligence, but according to Whitby the most mentioned idea about the goal of AI is provided by the Turing Test. This test is also called the

The purpose of this paper is to bring to light a fresh new perspective of Artificial Intelligence or simply (AI). There have been numerous endeavours to make artificial intelligence which is inclusive of frontiers such as neural network, evolution theory, and so forth, not forgetting that a number of current issues have found solutions in the application of these concepts, the case still remains that each theory only covers a certain isolated aspect of human intelligence. To date, he gap that stands between a human being and an artificial intelligence agent still remains unabridged. In this paper an extrapolated version of artificial intelligence shall be discussed which will be augmented by emotions and the plausibility of inheriting a neural architecture from one generation to the next in a bid to make artificial intelligence to compare to the natural behaviour and intelligence of human

What the author finds truly disturbing, however, is the threat of our brains being replaced by artificial intelligence. As the creators of Google admitted, their ultimate goal is to give people access to all the information available on the Internet by connecting their brains to artificial intelligence system. For Carr, such ambition suggest that intelligence can be boiled down to a mechanical process that will leave no place for critical thinking, creativity and personal reflection.

Society today is greatly influenced by technology and the impact it has had within the past 20 years. One of the largest breakthroughs, though, is Artificial Intelligence (A.I.). The technology associated with A.I. has greatly developed in the past years, and is only making devices smarter. When someone mentions technology, or even the technological breakthroughs the world has gone through recently, many people go straight to smartphones and computers. A.I. is often overlooked, or put into a general category of "technology". Yet, artificial intelligence is something that should we not be so quick to dismiss, and should be something that gets people talking and even excited for what the future holds.

Throughout its history, artificial intelligence has always been a topic with much controversy. Should human intelligence be mimicked? If so, are there ethical bounds on what computers should be programmed to do? These are a couple of question that surround the artificial intelligence controversy. This paper will discuss the pros and cons of artificial intelligence so that you will be able to make an educated decision on the issue.

This essay proved through a series of evidence that Brian Aldiss communicates in “Who Can Replace a Man” that machines are ultimately dependent on human intelligence. The machines argue logically but then shut down, obey human orders, and do not start working without receiving orders from the radio operated by

In today’s fast paced technologically savvy society, everyone wants the most advanced technology, this thirst for the next big thing is what makes technology fields the fastest changing and growing sectors. In countless movies, television shows, and novels, there is a representation of a humanoid character that is in fact a machine functioning and learning new skills with artificial intelligence. The problem with these shows is that the representation of modern day artificial intelligence is largely skewed, these machines have personalities and emotions making them relatable to humans when they are still just a very elaborate computer program. Artificial intelligence is the cognitive ability to solve problems, recognize patterns, and have

It is seen that computerized reasoning is assuming an extraordinary part in the research of advanced science and operational research regions.In the future intelligent machines will supplant human capacities in unimaginable way. Intelligence is generally considered as the capacity to learn and reason about information to take care of more complex issues.

Today, R and Python are the most popular open tools for Machine Learning. This Chapter presents a general overview of R and Python, their characteristics and usage for machine learning. Lastly, a comparison matrix of R and Python for ML is provided at the end of this chapter.

Artificial Intelligence is a topic within the public media that has existed for decades, but is now a concern due to the reality of human advancement and innovation in the field of science and technology. Many people believe that computers will become self-aware or sentient and view humanity as a disposable resource and gain supremacy. Reasoning that research on the technology should halt and not become more advance. Whereas others believe they will help catapult research and the economy forward, supporting the operations and innovations the technology offers. The complicated and divided solutions to the debate aren’t obvious, but there are more benefits to improving artificial intelligence than there is stopping it. Therefore, the negative effects people believe will occur can be resolved.

Data mining is the process of automatically discovering useful information from large data repositories [2]. The rapid advances in technologies led to accumulation of vast amount data. As the number of organizations grows day by day the breeding of new technologies and new styles of data also increases. It is difficult to handle them and store them in an efficient manner and of course retrieval of data is extremely challenging [3]. Nowadays we cannot use traditional methods to explore the data analysis because of the size of dataset. So it is very important to make study on data analysis. Most of the technologies are blended with data mining or we can say that data mining is vital and indispensible concept for every technology. Traditional machine learning algorithms like decision trees or artificial neural networks are examples of embedded approaches [9][10].Data mining tasks are mainly divided into predictive and descriptive. Predictive refers to predict the particular attribute based on other attributes. Descriptive task is to derive patterns like correlations, trends, clusters, trajectories and anomalies. Association analysis is used to discover patterns from correlated data and the output of analysis is represented using implication rules. Cluster analysis is the method of partitioning the datasets into different clusters and each cluster data is strongly correlated with intra-manner and inter clusters shows strong repulsion. There are several clustering methods but it

Weka (Waikato Environment for Knowledge Analysis) is a collection of machine learning algorithms developed on Java platform by University of Waikato, New Zealand. It is a data analyzing tool used for data modeling and predictive analysis. It is licensed under GNU General Public License. As it is implemented in Java it is platform independent. It is a comprehensive collection of various data preprocessing and modeling techniques. Some of the operations performed using Weka like classification, clustering etc. are discussed here. It provides implementation of various algorithms which can be applied on any kind of datasets.