Data Science Nigeria 2021 AI Bootcamp Qualification Hackathon by Data Science Nigeria
Sapa customer response prediction
Prize
Knowledge
Time
Ended ~1 year ago
Participants
524 active · 774 enrolled
Helping
Nigeria
Intermediate
Classification
Financial Services
Description

This is a private hackathon open to Data Science Nigeria AI+ members to qualify for the 2021 AI Bootcamp. If you would like to participate, please fill out the QUALIFICATION HACKATHON form here https://www.datasciencenigeria.org/2021-bootcamp/.

Sapa.com is one of the leading eCommerce platforms in Nigeria with millions of daily complete transactions. The goods and services on sapa.com cater for both the elite and the masses which makes it the first choice for almost everybody in Nigeria. Due to the COVID-19 pandemic that struck the entire world in all areas of living, the companies' daily complete transactions have dropped drastically to thousands.

The CEO, Mr Echoke in his recent actions to put the platform back to the top of the eCommerce platforms chain in the country has approved the use of Artificial intelligence in User Personality Analysis. The company has contracted your team consisting of AI professionals with a special focus on recommender system development to build a robust intelligent model capable of recommending products and services to Users based on their activities on sapa.com.

Your team lead has assigned you to the building of a model capable of predicting users’ responses to marketing campaigns based on the features in the provided dataset by the sapa.com data engineer. The next phase of the project is highly dependent on the accuracy of your model as this is the foundation of what will constitute the features of the proposed recommender system development. Good luck!

About Data Science Nigeria (datasciencenigeria.org)

Data Science Nigeria (DSN) is a non-profit run and managed by the Data Scientists Network Foundation. Our vision is to accelerate Nigeria’s development through a solution-oriented application of machine learning in solving social/business problems and to galvanize data science knowledge revolution, which can position Nigeria to become the outsourcing hub for international Data Science/Advanced Analytics/Big Data projects, with opportunity to access at least 1% share of the global big data and analytics market, valued at $150b in 2017 ($203b in 2020).

We adopt a practitioner-led model where experienced and hands-on data scientists in Nigeria and in the Diaspora train and mentor young Nigerians through face-to-face, virtual coaching classes, project-based support and holiday boot camps funded by individuals and corporate organizations.

Rules

This is a private hackathon open to Data Science Nigeria AI+ members to qualify for the 2021 AI Bootcamp. If you would like to participate, please fill out the QUALIFICATION HACKATHON form here https://www.datasciencenigeria.org/2021-bootcamp/.

Teams and collaboration

You may participate in competitions only as an individual.

Multiple accounts per user are not permitted, and neither is collaboration or membership between individuals. Individuals and their submissions originating from multiple accounts will be immediately disqualified from the platform.

Code must not be shared privately. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

You may use pretrained models as long as they are openly available to everyone.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party and you must be legally entitled to assign ownership of all rights of copyright in and to the winning solution code to Zindi.

Submissions and winning

You may make a maximum of 20 submissions per day and a total of 240 submissions over the course of the hackathon.

Before the end of the competition you need to choose 2 submissions to be judged on for the private leaderboard. If you do not make a selection your 2 best public leaderboard submissions will be used to score on the private leaderboard.

Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 30% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers the other 70% of the test dataset, will be made public and will constitute the final ranking for the competition.

Note that to count, your submission must first pass processing. If your submission fails during the processing step, it will not be counted and not receive a score; nor will it count against your daily submission limit. If you encounter problems with your submission file, your best course of action is to ask for advice on the Competition’s discussion forum.

If you are in the top 5 at the time the leaderboard closes, the host of this hackathon will reach out to you via the Zindi inbox to request your code. On receipt of the message, you will have 48 hours to respond and submit your code following the submission guidelines detailed below. Failure to respond will result in disqualification.

If two solutions earn identical scores on the leaderboard, the tiebreaker will be the date and time in which the submission was made (the earlier solution will win).

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Zindi is committed to providing solutions of value to our clients and partners. To this end, we reserve the right to disqualify your submission on the grounds of usability or value. This includes but is not limited to the use of data leaks or any other practices that we deem to compromise the inherent value of your solution.

Zindi also reserves the right to disqualify you and/or your submissions from any competition if we believe that you violated the rules or violated the spirit of the competition or the platform in any other way. The disqualifications are irrespective of your position on the leaderboard and completely at the discretion of Zindi.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

Reproducibility of submitted code

  • If your submitted code does not reproduce your score on the leaderboard, we reserve the right to adjust your rank to the score generated by the code you submitted.
  • If your code does not run you will be dropped from the top 10. Please make sure your code runs before submitting your solution.
  • Always set the seed. Rerunning your model should always place you at the same position on the leaderboard. When running your solution, if randomness shifts you down the leaderboard we reserve the right to adjust your rank to the closest score that your submission reproduces.
  • We expect full documentation. This includes:
  • All data used
  • Output data and where they are stored
  • Explanation of features used
  • A requirements file with all packages and versions used
  • Your solution must include the original data provided by Zindi and validated external data (if allowed)
  • All editing of data must be done in a notebook (i.e. not manually in Excel)
  • Environment code to be run. (e.g. Google Colab or the specifications of your local machine)
  • Expected run time for each notebook. This will be useful to the review team for time and resource allocation.

Data standards:

  • Your submitted code must run on the original train, test, and other datasets provided.
  • If external data is allowed, external data must be freely and publicly available, including pre-trained models with standard libraries. If external data is allowed, any data used should be shared with Zindi to be approved and then shared on the discussion forum. Zindi will also make note of the external data available on the data page.
  • Packages:
  • You must submit a requirements file with all packages and versions used.
  • If a requirements file is not provided, solutions will be run on the most recent packages available.
  • Custom packages in your submission notebook will not be accepted.
  • You may only use tools available to everyone i.e. no paid services or free trials that require a credit card.

Consequences of breaking any rules of the competition or submission guidelines:

  • First offence: No prizes for 6 months and 2000 points will be removed from your profile (probation period). If you are caught cheating, all individuals involved in cheating will be disqualified from the challenge(s) you were caught in and you will be disqualified from winning any competitions for the next six months and 2000 points will be removed from your profile. If you have less than 2000 points to your profile your points will be set to 0.
  • Second offence: Banned from the platform. If you are caught for a second time your Zindi account will be disabled and you will be disqualified from winning any competitions or Zindi points using any other account.
  • Teams with individuals who are caught cheating will not be eligible to win prizes or points in the competition in which the cheating occurred, regardless of the individuals’ knowledge of or participation in the offence.
  • Teams with individuals who have previously committed an offence will not be eligible for any prizes for any competitions during the 6-month probation period.

Monitoring of submissions

  • We will review the top 20 solutions of every competition when the competition ends.
  • We reserve the right to request code from any user at any time during a challenge. You will have 24 hours to submit your code following the rules for code review (see above). Zindi reserves the right not to explain our reasons for requesting code. If you do not submit your code within 24 hours you will be disqualified from winning any competitions or Zindi points for the next six months. If you fall under suspicion again and your code is requested and you fail to submit your code within 24 hours, your Zindi account will be disabled and you will be disqualified from winning any competitions or Zindi points with any other account.
Evaluation

The error metric for this competition is the F1 score, which ranges from 0 (total failure) to 1 (perfect score). Hence, the closer your score is to 1, the better your model.

F1 Score: A performance score that combines both precision and recall. It is a harmonic mean of these two variables. Formula is given as: 2*Precision*Recall/(Precision + Recall)

Precision: This is an indicator of the number of items correctly identified as positive out of total items identified as positive. Formula is given as: TP/(TP+FP)

Recall / Sensitivity / True Positive Rate (TPR): This is an indicator of the number of items correctly identified as positive out of total actual positives. Formula is given as: TP/(TP+FN)

Where:

TP=True Positive
FP=False Positive
TN=True Negative
FN=False Negative

For every row in the dataset, submission files should contain 2 columns: ID and target.

Your submission file should look like this:

ID            Response
ID_WGZRIT9     0
ID_UOFLGFN     0
ID_8F9K7D9     1
Prizes

This is a learning competition. Aside from knowledge, there are no prizes for this competition.

Timeline

Competition closes on 12 October 2021.

Final submissions must be received by 11:59 PM WAT.

We reserve the right to update the contest timeline if necessary.