Top 1200 Data Structures Quotes & Sayings - Page 4

We charted individual pitches by hand, so I had that data from game to game, but from year to year, I didn't really have that data, because a lot of times it was discarded.

The librarian isn't a clerk who happens to work in a library. A librarian is a data hound, a guide, a sherpa and a teacher. The librarian is the interface between reams of data and the untrained but motivated user.

While I'm driving, I've got speed, gear, lap time, water temperature, blood sugar, RPM, oil pressure. I've got car data and body data all together. It's all on the dash.

When people criticize me for not having any respect for existing structures and institutions, I protest. I say I give institutions and structures and traditions all the respect that I think they deserve. That's usually mighty little, but there are things that I do respect. They have to earn that respect. They have to earn it by serving people. They don't earn it just by age or legality or tradition.

In the increasingly digital world, data is a valuable currency, yet as consumers, we control and own little of it. As consumers, we must ask what big companies do with our data, a question directed to both the online and traditional ones.

There is so much data available to us, but most data won't help us succeed.

... while in theory digital technology entails the flawless replication of data, its actual use in contemporary society is characterized by the loss of data, degradation, and noise; the noise which is even stronger than that of traditional photography.

The only thing they [government] want is better data. But data doesn't tell people someone is well educated. It's a vicious circle. There is some myth involved. Some of this attitude has a long history.

I think I've read all of W.E.B. Du Bois, which is a lot. He started off with comprehensive field work in Philadelphia, publishing a book in 1899 called 'The Philadelphia Negro'. It was this wonderful combination of clear statistical data and ethnographic data.

I wonder what really goes on in the minds of Church leadership who know of the data concerning the Book of Abraham, the new data on the First Vision, etc.... It would tend to devastate the Church if a top leader were to announce the facts.

I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.

The fact that radio is so hopeless at delivering data makes it an uncluttered medium, offering the basic story without the detailed trappings. But it does mean that if data is important, radio is probably not your place.

Sense data are much more controversial than qualia, because they are associated with a controversial theory of perception - that one perceives the world by perceiving one's sense-data, or something like that.

I'm repledging myself to human-scale values. As a fiction writer, the best data comes through the senses and is then processed through many revisions. We have to learn to be intelligent assessors of the data coming in to us and what it's doing to our mental process.

What's going on in the game today... it's data vs. art - that's what it comes down to for me. Art being the human heartbeat, data being numbers, the math, etc. I believe there's a balance to be struck right there.

I am a data hound and so I usually end up working on whatever things I can find good data on. The rise of Internet commerce completely altered the amount of information you could gather on company behavior so I naturally drifted toward it.

When you have a large amount of data that is labeled so a computer knows what it means, and you have a large amount of computing power, and you're trying to find patterns in that data, we've found that deep learning is unbeatable.

Google is famous for making the tiniest changes to pixel locations based on the data it accrues through its tests. Google will always choose a spartan webpage that converts over a beautiful page that doesn't have the data to back it up.

We tend to assume that data is either private or public, either owned by one person or shared by many. In fact there's more to it than that, above and beyond the upsetting reality that private data is now anything but.

Big data has been used by human beings for a long time - just in bricks-and-mortar applications. Insurance and standardized tests are both examples of big data from before the Internet.

Integral to the orb is our low cost long-range wireless radio data system and a protocol that allows us to send this data over 90% of the US population every 15 minutes throughout the day.

Apple knows a lot of data. Facebook knows a lot of data. Amazon knows a lot of data. Microsoft used to, and still does with some people, but in the newer world, Microsoft knows less and less about me. Xbox still knows a lot about people who play games. But those are the big five, I guess.

When we think of globalization we are thinking in part of structures and institutions that have been developed over time and that have allowed us to become more interdependent and interrelated. But the development, the extraordinary development, of those structures and institutions has not fundamentally transformed our humanity. We are still those animals with fears and anxieties and insecurities in the face of death and dread and disappointment and disease.

Today, I think a CFO needs to be more of an operating CFO: someone who's using the financial data and the data of the company to help drive strategy, the allocation of capital, and the management of risks.

I have given no definition of love. This is impossible, because there is no higher principle by which it could be defined. It is life itself in its actual unity. The forms and structures in which love embodies itself are the forms and structures in which love overcomes its self-destructive forces.

Companies are getting bitten by hiring a data scientist who isn't really a data scientist.

Concepts are vindicated by the constant accrual of data and independent verification of data. No prize, not even a Nobel Prize, can make something true that is not true.

We are now at a point in time when the ability to receive, utilize, store, transform and transmit data - the lowest cognitive form - has expanded literally beyond comprehension. Understanding and wisdom are largely forgotten as we struggle under an avalanche of data and information.

The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.

Having a love ethic, as opposed to simply being in love, or having a lover, means love is the way you actively choose to engage with the world - whether you're in a relationship or not. It's not about disappearing into existing structures, norms, and privileges. It's precisely about breaking with the existing structures, values, and norms that prohibit real love in our culture.

A scientist naturally and inevitably ... mulls over the data and guesses at a solution. He proceeds to testing of the guess by new data-predicting the consequences of the guess and then dispassionately inquiring whether or not the predictions are verified.

The conversation people need to have is no longer about women assuming positions of leadership within the existing power structure, it's about the power structures themselves, it's about how to go about assuming power, how to change the structures.

Data is very important, but you have to be good at reading the data in an emotional way. If you look at a selling report, there's an emotional trend to what's selling.

By using big data, it will also be possible to predict adverse weather conditions, rerouting ships to avoid delays, and monitor fuel data, thereby allowing companies to optimize their supply chains and the way they drive their business.

I kept a notebook, a surreptitious journal in which I jotted down phrases, technical data, miscellaneous information, names, dates, places, telephone numbers, thoughts, and a collection of other data I thought was necessary or might prove helpful.

[Sovereignty] would break the American monopoly, but it would also break Internet business, because you'd have to have a data center in every country. And data centers are tremendously expensive, a big capital investment.

Where big data is all about seeking correlations - and thus to make incremental changes - small data is all about causations - seeking to understand the reasons why.

What I tend to do is blend quantitative with the qualitative to allow me to plot the qualitative data in some way. It's a question of what quantitative data are most applicable. So I'm playing with that, merging the two.

The paradigm shift of the ImageNet thinking is that while a lot of people are paying attention to models, let's pay attention to data. Data will redefine how we think about models.

My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.

Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data - big surfaces, deep depths - and not enough data - it is too expensive and not necessarily useful to collect samples of any kind from all over.

On all levels, evolution occurs in response to a crisis situation, not infrequently a life-threatening one, when the old structures, inner or outer, are breaking down or are not working anymore. On a personal level, this often means the experience of loss of one kind or another: the death of a loved one, the end of a close relationship, loss of possessions, your home, status, or a breakdown of the external structures of your life that provided a sense of security.

Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.

Every day, I absorb countless data bits through emails, phone calls, and articles; process the data; and transmit back new bits through more emails, phone calls, and articles. I don't really know where I fit into the great scheme of things and how my bits of data connect with the bits produced by billions of other humans and computers.

The problem with data is that it says a lot, but it also says nothing. 'Big data' is terrific, but it's usually thin. To understand why something is happening, we have to engage in both forensics and guess work.

Listening to the data is important... but so is experience and intuition. After all, what is intuition at its best but large amounts of data of all kinds filtered through a human brain rather than a math model?

I think philosophers can do things akin to theoretical scientists, in that, having read about empirical data, they too can think of what hypotheses and theories might account for that data. So there's a continuity between philosophy and science in that way.

The NSA is not listening to anyone's phone calls. They're not reading any Americans' e-mails. They're collecting simply the data that your phone company already has, and which you don't have a reasonable expectation of privacy, so they can search that data quickly in the event of a terrorist plot.

Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.

'Data exhaust' is probably my least favorite phrase in the big data world 'cause it sounds like something you're trying to get rid of or something noxious that comes out of the back of your car.

This is where the world is going: direct access from anywhere to any type of data, whether it's a small piece of data or a small answer but a long algorithm to create that answer. The user doesn't care about this.

We should have companies required to get the consent of individuals before collecting their data, and we should have as individuals the right to know what's happening to our data and whether it's being transferred.

Although someone's vote may hurt me by supporting the structures in place that hold people of colour, women, and LGBT+ people down, some people just don't realise that these structures exist. The way someone votes doesn't make them a bad person; it just means that, at the time, this was the best decision they thought they could make.

The conjuror or con man is a very good provider of information. He supplies lots of data, by inference or direct statement, but it's false data. Scientists aren't used to that scenario. An electron or a galaxy is not capricious, nor deceptive; but a human can be either or both.

I am what we call a 'karma yogi' in Sanskrit. A karma yogi is somebody who believes in data. I collect a lot of data.

Data by itself is not useful. Data is only useful if it can be applied for public benefit.

I tend to write poetry that is rich in data of various sorts. The lyric poem isn't perfectly suited to accommodating such data, so I've had to find new ways to say everything that I want to say.

This new large-scale spiritual awakening is occurring primarily not within the confines of the established religions, but outside of those structures. Some of it, however, is also happening within the existing churches and religious institutions wherever the members of those congregations do not identify with rigid and exclusive belief systems whose unconscious purpose is to foster a sense of separation on which the egoic mind structures depend for their survival.

Our problems are not with the data, itself, but arise from our interpretation of the data.

Facts and data, rather than opinion, are the two cornerstones of problem solving, and yet they are consistently withheld from the people by American media. We must have facts and data in order to recognize where there is a problem!