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Using TinEye , you can search by image or perform what we call a reverse image search. You can do that by uploading an image or searching by URL. You can also simply drag and drop your images to start your search. TinEye constantly crawls the web and adds images to its index.SEE VIDEO BY TOPIC: Find Unknown Person Name and Details With Just a Pictures - Simple Tricks
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- Find the tall girl - Picture of Blue Sky Cabo Fishing and Tours, Cabo San Lucas
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- Appeal to find girl, 15, missing from Dagenham
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- How a Math Genius Hacked OkCupid to Find True Love
- Finding a Facebook Profile From a Picture
Find the tall girl - Picture of Blue Sky Cabo Fishing and Tours, Cabo San Lucas
Chris McKinlay was folded into a cramped fifth-floor cubicle in UCLA's math sciences building, lit by a single bulb and the glow from his monitor. The subject: large-scale data processing and parallel numerical methods.
While the computer chugged, he clicked open a second window to check his OkCupid inbox. McKinlay, a lanky year-old with tousled hair, was one of about 40 million Americans looking for romance through websites like Match.
He'd sent dozens of cutesy introductory messages to women touted as potential matches by OkCupid's algorithms. Most were ignored; he'd gone on a total of six first dates. On that early morning in June , his compiler crunching out machine code in one window, his forlorn dating profile sitting idle in the other, it dawned on him that he was doing it wrong. He'd been approaching online matchmaking like any other user. Instead, he realized, he should be dating like a mathematician.
OkCupid was founded by Harvard math majors in , and it first caught daters' attention because of its computational approach to matchmaking. Members answer droves of multiple-choice survey questions on everything from politics, religion, and family to love, sex, and smartphones.
The closer to percent—mathematical soul mate—the better. But mathematically, McKinlay's compatibility with women in Los Angeles was abysmal. OkCupid's algorithms use only the questions that both potential matches decide to answer, and the match questions McKinlay had chosen—more or less at random—had proven unpopular.
When he scrolled through his matches, fewer than women would appear above the 90 percent compatibility mark. And that was in a city containing some 2 million women approximately 80, of them on OkCupid. On a site where compatibility equals visibility, he was practically a ghost.
He realized he'd have to boost that number. If, through statistical sampling, McKinlay could ascertain which questions mattered to the kind of women he liked, he could construct a new profile that honestly answered those questions and ignored the rest.
He could match every woman in LA who might be right for him, and none that weren't. He then sorted female daters into seven clusters, like "Diverse" and "Mindful," each with distinct characteristics. Maurico Alejo. Even for a mathematician, McKinlay is unusual. Raised in a Boston suburb, he graduated from Middlebury College in with a degree in Chinese.
In August of that year he took a part-time job in New York translating Chinese into English for a company on the 91st floor of the north tower of the World Trade Center. The towers fell five weeks later. McKinlay wasn't due at the office until 2 o'clock that day.
He was asleep when the first plane hit the north tower at am. The experience kindled his interest in applied math, ultimately inspiring him to earn a master's and then a PhD in the field.
Now he'd do the same for love. First he'd need data. While his dissertation work continued to run on the side, he set up 12 fake OkCupid accounts and wrote a Python script to manage them.
To find the survey answers, he had to do a bit of extra sleuthing. OkCupid lets users see the responses of others, but only to questions they've answered themselves. McKinlay watched with satisfaction as his bots purred along. Then, after about a thousand profiles were collected, he hit his first roadblock.
OkCupid has a system in place to prevent exactly this kind of data harvesting: It can spot rapid-fire use easily. One by one, his bots started getting banned.
He turned to his friend Sam Torrisi, a neuroscientist who'd recently taught McKinlay music theory in exchange for advanced math lessons. Torrisi was also on OkCupid, and he agreed to install spyware on his computer to monitor his use of the site. With the data in hand, McKinlay programmed his bots to simulate Torrisi's click-rates and typing speed. He brought in a second computer from home and plugged it into the math department's broadband line so it could run uninterrupted 24 hours a day.
After three weeks he'd harvested 6 million questions and answers from 20, women all over the country. McKinlay's dissertation was relegated to a side project as he dove into the data. He was already sleeping in his cubicle most nights. Now he gave up his apartment entirely and moved into the dingy beige cell, laying a thin mattress across his desk when it was time to sleep.
For McKinlay's plan to work, he'd have to find a pattern in the survey data—a way to roughly group the women according to their similarities. The breakthrough came when he coded up a modified Bell Labs algorithm called K-Modes. First used in to analyze diseased soybean crops, it takes categorical data and clumps it like the colored wax swimming in a Lava Lamp.
With some fine-tuning he could adjust the viscosity of the results, thinning it into a slick or coagulating it into a single, solid glob. He played with the dial and found a natural resting point where the 20, women clumped into seven statistically distinct clusters based on their questions and answers.
He retasked his bots to gather another sample: 5, women in Los Angeles and San Francisco who'd logged on to OkCupid in the past month. Another pass through K-Modes confirmed that they clustered in a similar way. His statistical sampling had worked. Now he just had to decide which cluster best suited him. He checked out some profiles from each. One cluster was too young, two were too old, another was too Christian. But he lingered over a cluster dominated by women in their mid-twenties who looked like indie types, musicians and artists.
This was the golden cluster. The haystack in which he'd find his needle. Somewhere within, he'd find true love. Actually, a neighboring cluster looked pretty cool too—slightly older women who held professional creative jobs, like editors and designers. He decided to go for both. He'd set up two profiles and optimize one for the A group and one for the B group. He text-mined the two clusters to learn what interested them; teaching turned out to be a popular topic, so he wrote a bio that emphasized his work as a math professor.
The important part, though, would be the survey. He picked out the questions that were most popular with both clusters.
He'd already decided he would fill out his answers honestly—he didn't want to build his future relationship on a foundation of computer-generated lies.
But he'd let his computer figure out how much importance to assign each question, using a machine-learning algorithm called adaptive boosting to derive the best weightings. With that, he created two profiles, one with a photo of him rock climbing and the other of him playing guitar at a music gig. Sex or love? Answer: Love, obviously. But for the younger A cluster, he followed his computer's direction and rated the question "very important.
When the last question was answered and ranked, he ran a search on OkCupid for women in Los Angeles sorted by match percentage. At the top: a page of women matched at 99 percent. He scrolled down Ten thousand women scrolled by, from all over Los Angeles, and he was still in the 90s. He needed one more step to get noticed. Women reciprocated by visiting his profiles, some a day.
And messages began to roll in. Thought I'd say hi. The math portion of McKinlay's search was done. Only one thing remained. He'd have to leave his cubicle and take his research into the field. He'd have to go on dates.
Sheila was a web designer from the A cluster of young artist types. They met for lunch at a cafe in Echo Park. By the end of his date with Sheila, it was clear to both that the attraction wasn't there. He went on his second date the next day—an attractive blog editor from the B cluster.
He'd planned a romantic walk around Echo Park Lake but found it was being dredged. She'd been reading Proust and feeling down about her life. Date three was also from the B group. He met Alison at a bar in Koreatown. She was a screenwriting student with a tattoo of a Fibonacci spiral on her shoulder.
McKinlay got drunk on Korean beer and woke up in his cubicle the next day with a painful hangover. He sent Alison a follow- up message on OkCupid, but she didn't write back. The rejection stung, but he was still getting 20 messages a day. Dating with his computer-endowed profiles was a completely different game. He could ignore messages consisting of bad one-liners.
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Jon King. Jessica was last seen at 7. She was wearing her school uniform of black trousers, a light blue top, red jacket and red and black trainers.
Does your child have trouble getting the right words out, following directions, or being understood? In this revised new edition of Childhood Speech, Language, and Listening Problems , speech-language pathologist Patricia Hamaguchi-who has been helping children overcome problems like these for more than thirty years-answers your questions to help you determine what's best for your child. More than 1. If your child is one of them, this book gives you the crucial and up-to-date guidance you need to help him or her both in school and at home. Childhood Speech, Language, and Listening Problems.
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VSCO is a place where expression matters most. We offer creative photo and video editing tools, inspiration, and a place for you to be you. Easily import and edit your RAW photos. Use editing tools like Contrast and Saturation to make your photos pop or use Grain and Fade to add texture and mimic analog film effects. Adjust or play around with your photo perspectives with Crop and Skew. Save and recreate your favorite edits with Recipes. Frame your images with a touch of color using Borders. Adjust white balance and experiment with color control with HSL.
Appeal to find girl, 15, missing from Dagenham
Did you have picture of someone and want to know more about them? Maybe you'd like to know their name, birth date, email address, where they work, or if they're single. Using the method described below, you may be able to find their Facebook profile, and if they've made the information you want public, you'll find the answers you're looking for. Now you try.
Nub theory explained: Predict your baby’s sex at 12 weeks
You can share photos, videos, albums, and movies with any of your contacts, even if they don't use the Google Photos app. You can share to anyone with a Google Account if they are in your contacts or by searching using their email address or phone number. To make sharing easier, Google suggests people to share with based on your interactions. You can also automatically share your entire library with someone.SEE VIDEO BY TOPIC: Can you find hidden women's in these 10 pictures? Only genius can see
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TEST: Can you find the girl in the photo? Hardly anyone can spot her!
Chris McKinlay was folded into a cramped fifth-floor cubicle in UCLA's math sciences building, lit by a single bulb and the glow from his monitor. The subject: large-scale data processing and parallel numerical methods. While the computer chugged, he clicked open a second window to check his OkCupid inbox. McKinlay, a lanky year-old with tousled hair, was one of about 40 million Americans looking for romance through websites like Match. He'd sent dozens of cutesy introductory messages to women touted as potential matches by OkCupid's algorithms. Most were ignored; he'd gone on a total of six first dates. On that early morning in June , his compiler crunching out machine code in one window, his forlorn dating profile sitting idle in the other, it dawned on him that he was doing it wrong. He'd been approaching online matchmaking like any other user.
Finding the right girl for a great relationship isn't easy. How do you discover the "one" for you? Knowing who you are, understanding what you want and searching in the right places are all key factors in finding your Ms.
How a Math Genius Hacked OkCupid to Find True Love
Finding a Facebook Profile From a Picture