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Kaggle has just given birth to the youngest Grandmaster in history, 17-year-old British high school student Mikel Bober-Irizar. His school does not have courses related to AI and machine learning, and all knowledge is self-study online. Kaggle was founded eight years ago and has more than 100 million registered users. Currently, there are only 122 Grandmasters. Mikel has achieved this result after three years of self-study, which is a formidable prospect. , but also inspiring. As long as you are willing, you can become a top Kaggle player through self-study.
There should be no one in the AI and big data circles who doesn’t know Kaggle. It is one of the best in the world.A platform for data science, machine learning competitions and distribution to friends. When it was acquired by Google last year, it once caused a stir in the industry. Companies and researchers can publish data, host and participate in competitions on the Kaggle platform, and generate the best models through “crowdsourcing”. The number of registered users now exceeds 1 million.
In the Kaggle Competitions rankings, there is a title that many users yearn for, and that is “Kaggle Grandmaster”, a top expert ranked 0.1‰.
In addition to representing you and participating in many competitions and winning many championships, this title is also very attractive when submitting resumes and looking for jobs. At the same time, you can also get bonuses by participating in large-scale competitions held by large companies. Ethiopians Escort
Just now, Kaggle CTO Ben Hamne Ethiopia Sugarr tweeted to celebrate Mikel Bober-Irizar, a 17-year-old boy from the UK, becoming the youngest Kaggle Grandmaster in history:
How the youngest Grandmaster in history was made
Currently, Kaggle has only 122 Grandmasters worldwide, and the current number one is a user who joined 8 years ago. ET Escorts
Mikel ranks 31st among the 122 Grandmasters. He spent 3 years. More importantly, , his knowledge of AI and machine learning is self-taught by searching and collecting information.
In Kaggle, it is very difficult to become a Grandmaster. The title Ethiopia Sugar is based on Kaggle Ethiopia Sugar DaddyProgression System to identify. It is a user level ranking system, which is similar to completing tasks in a game, defeating monsters, accumulating experience, and exchanging accumulated points to reach a certain level Ethiopia Sugarcan be upgraded after requesting it.
KaggThe grades of le Progression System from low to high are: Novice, Contributor, Expert, Master and Grandmaster.
Novice joins the community and is done by registering.
Based on the above, you still need to complete: add the user’s resume, positioning, personal work, and organization; confirm the account via SMS; run a script, complete a complete submission, comment once, and vote once to become a contributor. .
If a user has completed a large number of tasks on Kaggle in one or more specialized research categories, once the user reaches the expert level in a certain category, the user can enter the Kaggle Expert ranking.
If you can achieve the following results, you can obtain the title of Master:
The top Grandmaster needs to achieve the following goals, which is also called Virtual reality is a “top master” in a specialized field of research.
It can be seen that the requirements for achieving GraEthiopians Escortndmaster’s goals are still quite high, so let’s Find out what achievements this 17-year-old magical boy has achieved:
As you can see, Mikel Bober-Irizar has achieved a total of 6 medals Ethiopia Sugar Daddy gold medals, including 5 team battle gold medals and 1 solo gold medal.
Not only that, this young player participated in a total of 57 games, including 47 solo games (82%) and 10 team games (18%). It can be seen that Mikel Bober-Irizar is a strong seed player who can grow in team battles and solo in many aspects.
Looking at the Kaggle Competitions rankings, many GrandmasteEthiopians Sugardaddyr’s scores are much higher than this little British boy. Some What’s more, the number of gold medals has reached as many as 41.
But the point is that Mikel Bober-Irizar is only 17 years old. It can also be seen from the information that he joined Kaggle three years ago. In other words, he started programming, eating, and participating in competitions when he was 14 years old. , even earlier!
It can really be said that “the bones are astonishing, there is no one in ten thousand”He is a “martial arts wizard”!
Mikel Bober-Irizar is not only talented, but more importantly, diligent and extraordinary.
Judging from the above data, in the past three years, the little boy has an average annual meal and participation The number of competitions is 19, and the workload can be said to be quite sufficient. Looking back, can many students today achieve such a workload in a year?
And the workload of the recent magical boys? News has been emerging recently: from an 18-year-old boy being hired by Google to a 12-year-old girl writing cellular automation programs, Python has now been included in primary school curricula. “Old people” are all photographed on the beach!
He has not studied or participated in any formal AI courses, relying on self-taught skills
According to public data on Mikel’s LinkedIn homepage, Mikel Bober-Irizar studied at Royal Grammar School, Guildford, England, has been actively involved in the research and development of software and hardware for machine learning and autonomous driving technology since high school. It once led a team in Silicon ValleyEthiopia Sugar worked at Voyage, a self-driving taxi company, and later was responsible for back-end and server development at EduNow in the UK.
He is one of the first batch to obtain the Udacity autonomous vehicle engineer nanodegree One of the 500 people certified, there are more than 11,000 applicants for this degree, and the selection rate is less than 5%.
Although he is only 17 years old, Mikel is now a computer vision research and development intern at Mitsubishi Electric Research Laboratory (MERL). student, focusing on image analysis and representation learning. Previously, he served as the technical director of EduNow, a company that provides course review materials, paper research and study note services.
The following is about Mikel’s teaching and work on LinkedIn. Detailed information on what happened:
Mitsubishi Electric Research Laboratory (MERLET Escorts) Computer Vision Research Trainee
July 2018 – present
Mainly researches image analysis and representation learning
Technical director of EduNow Company
September 2017 – July 2018
Involved from scratch Build the EduNow platform, mainly responsible for back-end and server development
Voyage
July 2017
Development of various software and hardware projects for Voyage self-driving taxis
Udacity
September 2016-2017In June 2019
the first batch of 500 people (11,000 applicants) obtained the autonomous vehicle engineering Ethiopians Escort micro degree (Nanodegree), was invited to serve as one of the five student leaders of the course.
Brilliant results in the Kaggle Challenge
Google Landmark Search Challenge
In May 2018, a total of 209 teams participated and won the first place
This competition is for Contestants provide Ethiopia Sugar Daddy query images, and for each query, hope to retrieve similar landmarks in the database (if any) of all images.
The new dataset used in the competition is the world’s largest image retrieval research dataset, including more than 1 million images of unique landmarks. Image retrieval is a fundamental problem in computer vision, and is particularly important for querying images containing landmarks, since most of the photos people like to take contain these landmarksEthiopians Escort.
This challenge was held together with the “Landmark Recognition Challenge” (in this competition, Mikel ranked 33rd among 483 people, Top 7%). The test sets used in the two challenges are the same, encouraging more players to participate in the competition. However, there are no common landmarks between the training/retrieval sets of the two challenges.
Avito Duplicate Marketing Detection Challenge
In July 2016, 548 teams participated and won 2nd place (Top 1%)
Avito is the world’s largest and fastest-growing online marketing company One of the category marketers, this competition requires Kaggle contestants to develop a model that can automatically identify Ethiopia Sugar Daddy. Due to fierce competition, sellers often struggle to get their products tracked, which may mean posting the same marketing message multiple timesEthiopians Sugardaddy For sales, make slight modifications to the marketing text, or include photos of the product taken from different angles. Ethiopians Sugardaddy undergoes more accurate detection of duplicate marketing, Avito will make it easier for buyers to find honest sellers with whom to conduct their next transaction.
Bosch Childbirth Thread Fault Prediction Challenge
In November 2016, 627 teams participated and won 5th place (Top 1%)
In this challenge, Bosch requires participants to use Thousands of measurements and tests are performed on every component on the birth line to predict internal failures of the machine. This will allow Bosch to provide end users with high-quality products at the lowest cost.
The competition uses real recorded data from Bosch at every step in its assembly process, so advanced analytics can be used to improve these manufacturing processes. However, the complexity of the data and the complexity of the childbirth line have brought problems to the current method.
From an application perspective, it is more important to understand the principles of algorithmic tasks than to understand mathematics
In July 2017, Mikel said in an interview that in the end, he only came to eat and participate in the Kaggle challenge with the attitude of giving it a try. of. From the perspective of practical application, understanding the working principle of the algorithm is more important than its mathematical principle. His high school, the Royal Liberal Arts School, did not set up systematic courses in AI and machine learning. Mikel’s programming skills in machine learning and artificial intelligence were almost completely self-taught.
“There are many free courses online, but I don’t actually attend these courses. When I encounter a big problem that I want to solve, all I want to do is search for this on Google topic. I saw Kaggle on the Internet, and I thought, why not give it a try? “
“I don’t understand all the mathematical principles behind the algorithm, but in terms of practical applications, I think it is very important to the task method of the algorithm. It’s more important to have a reasonable understanding. Even if I can’t write the algorithm from scratch, I still understand what it does specifically, which helps me understand where the algorithm can be effective.”
Mikel also on Medium. It is relatively lively. At the beginning of this year, Xinzhiyuan also reported his evaluation article on CPU vulnerabilities: [Up to 40% reduction] Actual measurement of the impact of CPU vulnerability patches on machine learning and deep learning performance
Original title: 17 years old! The youngest Grandmaster in the history of Kaggle was born: Reached the top after 3 years of self-study in high school
Article source: [Microelectronic signal: AI_era, WeChat public account: Xinzhiyuan] Welcome to add follow-up attention! Please indicate the source when transcribing and publishing the article.
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