AmExpert 2018 (Machine Learning Hackathon)
About the Event
Introduction:
American Express and Analytics Vidhya presents “AmExpert”. An amazing opportunity to showcase your analytical abilities and talent.
Get a taste of the kind of challenges we face here at American Express on day to day basis.
MacBooks are up for grabs! Best performers also get a chance to get interviewed by American Express for analytics roles!!
Don’t hold on to the buzzing ideas in your mind. Just wear your thinking hats and display the spectrum of your creativity!
About the Company:
American Express is a globally integrated payments company, providing customers with access to products, insights and experiences that enrich lives and build business success. It is
- One of the world's most recognizable brands
- An exceptionally strong heritage - over 160 years of leadership and reinvention
- World's largest card issuer by purchase volume
- Recognized as the most innovative company in our industry
- Cutting-edge Information Management and unique Closed-Loop network
- Customer loyalty experts with industry-leading rewards programs and platforms
- A rich history and a bright future
Learn more at americanexpress.com/in and connect with us on:
Great Place to work:
Who can apply?:
Open for all data enthusiasts – statisticians, data scientists, analysts and students
Prizes:
1st: 15-inch MacBook Pro with Touch Bar: 2.8GHz quad-core i7, 256GB
2nd: 13-inch MacBook Pro: 2.3GHz dual-core i5, 256GB
3rd: 13-inch MacBook Air: 1.8GHz dual-core Intel Core i5, 128GB
In addition to the above, highest scorers get a chance to interview with American Express for analytical & machine learning roles
Rules:
- Entries submitted after the contest is closed, will not be considered
- Since this is a hiring hack, you are expected to solve the problem on your own
- Multiple IDs of user leads to disqualification from contest
- Use of external data is not allowed
- Participant must update their profile details and upload their latest CV
- Decision on the winners and runners-up made by American Express will be final and binding
- Throughout the hackathon, you are expected to respect fellow hackers and act with high integrity
- Analytics Vidhya and American Express hold the right to disqualify any participant at any stage of competition if participant(s) are deemed to be acting fraudulently.
- Total AV points to be awarded are 1000.
- Existing American Express employees are not allowed to participate in the competition
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Hear From Our Community
Best Knowledge Portal for Data Science
AV is one of the best knowledge portal for Data Science I know about and certainly the best in India. It caters to the need of all sorts of people, from beginners to well experienced professionals. The articles are in-depth in nature and cover wide-variety as well which is very difficult to find else where. Discuss portals help people to clarify their doubts while hackathons give a flavor of real world experience. Thank you AV and keep up the good work.!
Excellent Opportunity for Anyone
Analytics Vidhya hackathons are an excellent opportunity for anyone who is keen on improving and testing their data science skills. The portal offers a wide variety of state of the art problems like – image classification, customer churn, prediction, optimization, click prediction, NLP and many more. I have participated in many hackathons and they have been a significant contributor in improving my machine learning skills. These hackathons have real time submission and evaluation feature and you can always feel the competition heat on the leader-board. Hackathons also provide an immense opportunity for learning from other’s, as winner’s approach and code is shared at the end of the hackathon. I won the Barcelona water demand prediction hackathon and it boosted my confidence and network significantly.
Learnt a Lot
I learnt a lot by participating in various Hackathons conducted by Analytics Vidhya during last three years. One obvious benefit is given a dataset I can intuitively understand what works best which I apply in real life problems efficiently. My strategy in any Hackathon is to understand the dataset, feature engineering and cross validation. I try ensembling, hyper parameter tuning or stacking only if I have time. I believe feature engineering and cross validation is more important than your choice of algorithms.
My Guide and Mentor
I started my journey in analytics in August 2014 through an online course. Then came AV which gave a newbie like me a platform when my first article was published.Thereafter the association with AV has grown to AV being my guide and mentor. There is no dearth of analytics resources on the web but when you get it from experts in the Indian analytics space with a clear business problem in mind-there is nothing like it.The easy to understand language used to explain the most complex of subjects in data science is one of the cornerstones of the AV blog.The one place I know I will find answers to my questions and gain knowledge is AV. In the language of Data Science AV is an ensemble of many experts which bring out what is best for the community. :)
Thinking out of box
Right from college, I liked to participate in competitions and Analytics Vidhya helped me compete amongst the finest people. Now, even as I'm working as a full time data scientist, I still like to give it my best during these short yet intense competitions as it helps me think out of the box and get the best out of myself. I usually start with looking at the data and checking the distribution of features and target variables which involves a lot of group by commands. Once I settle for an initial feature set, I train a basic model to see where I am in the leaderboard. From there on it can go to completely revamping the model to use some new methodologies or tuning the model and features.
Spaces You Can Join
Data Science
Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!
10.4K
Generative AI
Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!
10.4K
Data Engineering
Over here, you can engage in discussions, ask questions, share insights, and converse about all things Data Science, from regression models to LLMs!
10.4K
Frequently Asked Questions
Find the answers for the most frequently asked questions
There are no specific requirements to register for the hackathon, although it is recommended to have some basic knowledge of the relevant topics, such as Data Science, Machine Learning, or Deep Learning, along with proficiency in a coding language, preferably Python.
Depending on the type of competition, you can participate individually or in a team.
You can access the problem statement under the "Problem Statement" tab once the Hackathon is live.
Participants benefit from one-on-one feedback, publication on a respected platform, recognition from a global audience, and monetary rewards for each published article. Additionally, the top articles receive special rewards.
Each article must be original, and pass plagiarism and not AI generated content checks. You can submit multiple articles as long as each is distinct. Proper citation of all references and image sources is mandatory.
In the Blogathon, an article typically explores a specific topic or idea within Data Science or Generative AI and is required to be at least 1000 words long. A guide, on the other hand, is a more comprehensive resource, covering all aspects of a particular subject in data science, and must be at least 2500 words long. Guides aim to serve as a one-stop resource, providing detailed insights and practical applications, whereas articles might focus on narrower or more specific topics.
Multiple submissions of the same article are prohibited and could lead to disqualification. Articles failing to meet the required length, originality, or citation standards will be rejected.
AVCC is a community for authors who have had three or more articles published in the Blogathons. Members benefit from monetary rewards for each published article and get the opportunity to showcase their work to a larger audience.
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