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Name: Aryia Behroziuan

Type: User

Company: QitSource

Bio: Artificial intelligence and data mining programmer and specialist working on genetics and in-depth learning projects and natural language processing and compute

Twitter: aryiabehroziuan

Location: IRAN

Blog: https://aryia-behroziuan.github.io/web/

Aryia Behroziuan's Projects

Artificial intelligence From Wikipedia, the free encyclopedia Jump to navigationJump to search "AI" redirects here. For other uses, see AI (disambiguation) and Artificial intelligence (disambiguation). Part of a series on Artificial intelligence Major goals[show] Approaches[show] Philosophy[show] History[show] Technology[show] Glossary[show] vte Artificial intelligence (AI), is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals. Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving".[4] As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect.[5] A quip in Tesler's Theorem says "AI is whatever hasn't been done yet."[6] For instance, optical character recognition is frequently excluded from things considered to be AI,[7] having become a routine technology.[8] Modern machine capabilities generally classified as AI include successfully understanding human speech,[9] competing at the highest level in strategic game systems (such as chess and Go),[10] autonomously operating cars, intelligent routing in content delivery networks, and military simulations.[11] Artificial intelligence was founded as an academic discipline in 1955, and in the years since has experienced several waves of optimism,[12][13] followed by disappointment and the loss of funding (known as an "AI winter"),[14][15] followed by new approaches, success and renewed funding.[13][16] For most of its history, AI research has been divided into sub-fields that often fail to communicate with each other.[17] These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"),[18] the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences.[21][22][23] Sub-fields have also been based on social factors (particular institutions or the work of particular researchers).[17] The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects.[18] General intelligence is among the field's long-term goals.[24] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields. The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it".[25] This raises philosophical arguments about the mind and the ethics of creating artificial beings endowed with human-like intelligence. These issues have been explored by myth, fiction and philosophy since antiquity.[30] Some people also consider AI to be a danger to humanity if it progresses unabated.[31][32] Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.[33] In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.[34][16]

ai-content

"Computing Machinery and Intelligence"

ai-move

Application of rail systems using artificial intelligence in industries

an-ann

An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68]

aneshsara

application

In 2006, the media-services provider Netflix held the first "Netflix Prize" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model to win the Grand Prize in 2009 for $1 million.[76] Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[77] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[78] In 2012, co-founder of Sun Microsystems, Vinod Khosla, predicted that 80% of medical doctors' jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[79] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognized influences among artists.[80] In 2019 Springer Nature published the first research book created using machine learning.[81]

applications

Main article: Applications of artificial intelligence AI is relevant to any intellectual task.[192] Modern artificial intelligence techniques are pervasive[193] and are too numerous to list here. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect.[194] High-profile examples of AI include autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art (such as poetry), proving mathematical theorems, playing games (such as Chess or Go), search engines (such as Google search), online assistants (such as Siri), image recognition in photographs, spam filtering, predicting flight delays,[195] prediction of judicial decisions,[196] targeting online advertisements, [192][197][198] and energy storage[199] With social media sites overtaking TV as a source for news for young people and news organizations increasingly reliant on social media platforms for generating distribution,[200] major publishers now use artificial intelligence (AI) technology to post stories more effectively and generate higher volumes of traffic.[201] AI can also produce Deepfakes, a content-altering technology. ZDNet reports, "It presents something that did not actually occur," Though 88% of Americans believe Deepfakes can cause more harm than good, only 47% of them believe they can be targeted. The boom of election year also opens public discourse to threats of videos of falsified politician media.[202

autonomous-vehicles

One of the newer application areas is autonomous vehicles, which include submersibles, land-based vehicles (small robots with wheels, cars or trucks), aerial vehicles, and unmanned aerial vehicles (UAV). The level of autonomy ranges from fully autonomous (unmanned) vehicles to vehicles where computer-vision-based systems support a driver or a pilot in various situations. Fully autonomous vehicles typically use computer vision for navigation, e.g. for knowing where it is, or for producing a map of its environment (SLAM) and for detecting obstacles. It can also be used for detecting certain task specific events, e.g., a UAV looking for forest fires. Examples of supporting systems are obstacle warning systems in cars, and systems for autonomous landing of aircraft. Several car manufacturers have demonstrated systems for autonomous driving of cars, but this technology has still not reached a level where it can be put on the market. There are ample examples of military autonomous vehicles ranging from advanced missiles to UAVs for recon missions or missile guidance. Space exploration is already being made with autonomous vehicles using computer vision, e.g., NASA's Curiosity and CNSA's Yutu-2 rover.

bayesian-networks

A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform inference and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams

blheli-master

boot-grub

How do I boot my PC from GRUB? [duplicate] Asked 3 years, 4 months ago Active 2 years, 5 months ago Viewed 107k times 16 12 This question already has answers here: How can I repair grub? (How to get Ubuntu back after installing Windows?) (14 answers) Closed 2 years ago. I can no longer boot Ubuntu following a corruption problem initially reported here (How do I solve the "invalid arch dependent elf magic" error message). When I power my laptop, I now get the following message: GNU GRUB version 2.02~beta2-9ubuntu1.7 Minimal BASH-like line editing is supported. For the first word, TAB lists possible command completions. Anywhere else TAB lists possible device or file completions." and then the prompt grub> Can anyone help me get back to Ubuntu ? boot grub2 share improve this question follow edited Jul 2 '17 at 18:17 You'reAGitForNotUsingGit 13.4k99 gold badges3838 silver badges7373 bronze badges asked Jun 28 '17 at 7:49 Mons 15911 gold badge33 silver badges77 bronze badges Comments are not for extended discussion; this conversation has been moved to chat. – Thomas Ward♦ Jul 2 '17 at 19:03 Big thumbs up to everybody. I chased down a few leads and finally solved the problem by booting from a live CD and entering the command "sudo update-grub" @derHugo your help was massively useful. – Mons Jul 2 '17 at 19:29 1 The various hints given by @derHugo can be found on the chat site on Stack Exchange here: chat.stackexchange.com/rooms/61451/… and in particular when he recommended googling the question, here: "Haha sorry always forget that ^^ anyway please Google it there are tons of articles addressing this issue e.g. here is another one". Anyway, I'm absolutely made up to be up and running on my laptop again. I know I'm not supposed to say thanks, but I will all the same. THANKS ! – Mons Jul 2 '17 at 21:59 add a comment 3 Answers 35 Ok, from grub type ls (hd0,1)/ you should see a file named vmlinuz or linux, and initrd.img Type linux (hd0,1)/vmlinuz root=/dev/sda1 or linux (hd0,1)/linux root=/dev/sda1 depending on what you found with ls (hd0,1)/, then: initrd (hd0,1)/initrd.img boot If you get initramfs rescue mode enter your password, then startx. You should now have a desktop. Use gparted to check your file system, if it reports an error, then you need to boot from a LiveCD or other media to fix it .... DO NOT attempt to repair a mounted partition. The following three commands fix many grub boot problems. They run quick so just do all three instead of trying to find which one you need. sudo grub-install /dev/sda && sudo update-grub && sudo update-initramfs -u Reboot and see what you get. share improve this answer follow edited Feb 2 '18 at 5:55 answered Jul 2 '17 at 18:49 ravery 6,11955 gold badges1616 silver badges3535 bronze badges 3 Is it really innitrd or should it be initrd? – WinEunuuchs2Unix Jul 2 '17 at 19:52 1 It is actually initrd – answerSeeker Jul 2 '17 at 20:19 1 @ravery Yes I could have corrected the typo. I have a weird point of view thinking it's more polite to point out to the author and letting them make the change. That way an otherwise spotless answer doesn't have the "blemish" of an "edited by someone else" flag. I do edit new users' questions frequently though... Have another +1 :) – WinEunuuchs2Unix Jul 2 '17 at 22:18 1 IF you stuck in "INITRAMFS" not in a fully booted system you can't use startx cause there is no desktop there, what you are referring as initramfs should be multi-user.target. – Ravexina♦ Jul 5 '17 at 8:53 3 In case the files above aren't listed, try iterating on ls (hd0,1)/ command, as in: ls (hd0,2)/, ls (hd0,3)/, etc. as suggested in here. – Nae Dec 23 '18 at 17:46 show 9 more comments 1 The most probable cause to that issue is installing the OS to a disk, grub to a different disk that is not removable. Then removing the OS disk. You could just plug the USB stick back in. Problem solved. share improve this answer follow edited Jul 2 '17 at 19:17 answered Jul 2 '17 at 19:02 RobotHumans 26.2k33 gold badges6969 silver badges109109 bronze badges Solution found (see above). – Mons Jul 2 '17 at 19:29 I saw the chat conversation. Solved with update-grub, which supports not refutes this answer. – RobotHumans Jul 2 '17 at 19:32 add a comment 1 Restart your system. Press f2 key while loading. Goto boot option. Press f5/f6 to change values (which os you want to install keep it in first place.). Enter f10 key....It may solve your problem. . . . If not enter this in grub rescue mode.... ls (hd0) (hd0,msdos6) (hd0,msdos5)....(hd0,msdos1) OR (hd0) (hd0,gpt6).....(hd0,gpt1) set boot=(hd0,gpt6) OR set boot=(hd0,msdos6) set prefix=(hd0,gpt6)/boot/grub OR use msdos6 instead. insmod normal normal This may solve your problem. share improve this answer follow answered Jul 9 '17 at 8:11 Pavan Rao 1122 bronze badges these are various ways to launch grub. this is not the issue as OP states. grub launches but drops to recovery mode. The issue is that the grub config file is missing – ravery Jul 9 '17 at 8:23 add a comment Not the answer you're looking for? Browse other questions tagged boot grub2 or ask your own question.

boston

The Boston Housing Dataset A Dataset derived from information collected by the U.S. Census Service concerning housing in the area of Boston Mass. BackUpDelve U of T -------------------------------------------------------------------- This dataset contains information collected by the U.S Census Service concerning housing in the area of Boston Mass. It was obtained from the StatLib archive (http://lib.stat.cmu.edu/datasets/boston), and has been used extensively throughout the literature to benchmark algorithms. However, these comparisons were primarily done outside of Delve and are thus somewhat suspect. The dataset is small in size with only 506 cases. The data was originally published by Harrison, D. and Rubinfeld, D.L. `Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978. Dataset Naming The name for this dataset is simply boston. It has two prototasks: nox, in which the nitrous oxide level is to be predicted; and price, in which the median value of a home is to be predicted Miscellaneous Details -Origin The origin of the boston housing data is Natural. -Usage This dataset may be used for Assessment. -Number of Cases The dataset contains a total of 506 cases. -Order The order of the cases is mysterious. -Variables There are 14 attributes in each case of the dataset. They are: CRIM - per capita crime rate by town ZN - proportion of residential land zoned for lots over 25,000 sq.ft. INDUS - proportion of non-retail business acres per town. CHAS - Charles River dummy variable (1 if tract bounds river; 0 otherwise) NOX - nitric oxides concentration (parts per 10 million) RM - average number of rooms per dwelling AGE - proportion of owner-occupied units built prior to 1940 DIS - weighted distances to five Boston employment centres RAD - index of accessibility to radial highways TAX - full-value property-tax rate per $10,000 PTRATIO - pupil-teacher ratio by town B - 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town LSTAT - % lower status of the population MEDV - Median value of owner-occupied homes in $1000's -Note Variable #14 seems to be censored at 50.00 (corresponding to a median price of $50,000); Censoring is suggested by the fact that the highest median price of exactly $50,000 is reported in 16 cases, while 15 cases have prices between $40,000 and $50,000, with prices rounded to the nearest hundred. Harrison and Rubinfeld do not mention any censoring.