Machine learning

artificial intelligence The artificial intelligence is one of branches in the computer science which is used in many application especially application of technology as it is the way that the machine or the computer or any application used to make its creation and creativity and help the application to take decisions like humans so it is used in making games, toys, computers, in the internet where the searching engines and absolutely in robotics. AI researchers and textbooks define the field of…

people concerned about the machines becoming far too powerful. Michael R. LaChat affirms this concern in his article titled “Artificial Intelligence and Ethics: An Exercise in the Moral Imagination,” stating that we must be careful to not overstep our boundaries and most notably “Don’t play God.” This fear, while supported by pop culture media, is already being accounted for. Industry professionals like Google’s DeepMind, build internal reset buttons to account for if the machines go rogue and…

with the advent of complex machine learning in artificial intelligence. These advancements, at the current rate, will change almost everything about…

what AI was compared to the one we know today. There was a proposal made to research AI at Dartmouth College in 1955 which stated: The study is to proceed on the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. (McCarthy, Minsky, Rochester & Shannon, 1955, p. 13) This idea of AI is the one we know today to be AGI. Unbeknownst to the researches at the time, the difficulty to…

Watson Watson is a computer system that was designed and built by IBM in order to compete on Jeopardy, an American TV quiz show, against human contestants at an expert level live on the show. Watson was named after IBM founder Thomas J. Watson. IBM Research have set out objectives to develop computer science with regard to pushing the boundaries of computer technology so as to advance the areas such as business, society and of course science. In order to achieve, this IBM Research took 3 years…

CASE STUDY: PREDICTIVE ANALYSIS MOUNIKA ENUGALA NORTHEASTERN UNIVERSITY  INTRODUCTION Predictive analysis is the process in the advanced analytics field which predicts the unknown scenarios in future. It uses lot of techniques like machine learning, data mining, probability and statistics, IT, data management etc. It brings down the results of previous input data searches and manages to understand the connections between the data thus identifying all the opportunities and risks of future which…

A COMPARITIVE STUDY OF NEAREST NEIGHBOUR ALGORITHM AND GENETIC ALGORITHM IN SOLVING TRAVELLING SALESMAN PROBLEM Ajaz Ahmed Khan Electronics and communication department SSGI FET Bhilai, India ajz70277@gmail.com Mrs. Himani Agrawal Electronics and communication department SSGI FET Bhilai, India Abstract—In this paper, we have used two algorithms, i.e. the Nearest Neighbor algorithm and Genetic Algorithm to solve the Travelling Salesman problem. The Travelling Salesman…

Assignment 3 Vinodh Kumar Sunkara, Microsoft Redmond, WA As part of this assignment, we’ve two main splits: 1.2.Running following clustering algorithms on two data sets a. K-Means clustering b. Expectation Maximization Running following dimensionality reduction algorithms a. PCA b. RCA c. ICA d. Any other feature selection algorithm: ISCA (Insignificant component analysis) I have used Weka for all my experiments. ICA wasn’t available in Weka and I installed the Students.Filters weka plugin…

Creativity and artificial intelligence Rishi Raj Sonar Student of MCA V MSIT, MATS University Raipur, Chhattisgarh E-mail:- banty.raj6@gmail.com Abstract Creativity or imagination is a fundamental feature of human intelligence, and a challenge for AI. AI used to create new ideas in three ways:- by producing novel combinations of familiar ideas; by exploring and by making transformations that enable the generation of previously impossible ideas. AI will have less trouble in…

diagnosis, fundus images are also used as general research tool. Several methods have been proposed in literature for segmentation of vessels. Several supervised methods include k-nearest neighbour classification[4], neural networks[6], support vector machines[5], decision tree[7], boosting of weak classifiers etc. Unsupervised methods include morphological processing[8]-[10], model based methods[11]-[13], matched filters or multi-scale methods[14]-[16]. This paper presents a method which is a…