This competition is open to all participants of the Ghana Data Science Summit (IndabaXGhana 2021), organized by Data Science Network in collaboration with Deep Learning Indaba. To join this competition, kindly apply for the Ghana Data Science Summit 2021 at http://bit.ly/indabaxgh21 (Only applicants of the conference will be eligible to take part in the competition) Applications close on Saturday, 3rd July, 2021.
This hackathon will run from 1 July to 15 July 2021.
When providing insurance, there are very few points of contact between customers and the insurance provider. Because of this, AutoInland (an Insurance company in west Africa with a focus on Auto Insurance) needs to make every point of contact count; one of the most valuable of these is filing and settlement of claims.
AutoInland believes that to achieve better service level standards, they need to anticipate future demands in terms of claims request volume. This will allow them to better manage their resources while keeping the customer experience positive and the levels of satisfaction high.
The objective of this hackathon is to develop a predictive model that determines if a customer will submit a vehicle insurance claim in the next three months. This solution will help streamline financial planning at AutoInland and allow them to better serve their customers by understanding which customers are likely to submit a claim.
A video tutorial and starter notebook are provided. https://www.indabaxghana.com/
About Data Science Network (datasciencenet.org)
The Data Science Network is a group of Ghanaian born Data Science Professionals who come together to organize regular summits, conferences, seminars, meet-ups, articles and webinars to create increased awareness and capacity building efforts in data science (Data Management, analytics, machine learning and Artificial Intelligence) and its application across business, academia and government. Our mission is to enable Ghana and Africa as a whole to harness the true value of data science and its application by creating awareness and building capacity through educative programs in Ghana as well as providing a medium for Data science professionals in Ghana to connect, share ideas and learn from each other. Our activities:
About IndabaX Ghana (indabaxghana.com)
IndabaX Ghana is a locally-organized Indaba (i.e gathering) that helps develop knowledge and capacity in machine learning and artificial intelligence in individual countries across Africa, and in this case, Ghana. A Deep Learning IndabaX is a locally-organized Indaba that helps spread knowledge and builds capacity in machine learning.
About Deep Learning Indaba (deeplearningindaba.com/2021)
The Deep Learning Indaba is an organisation whose mission is to Strengthen Machine Learning and Artificial Intelligence in Africa. We work towards the goal of Africans being not only observers and receivers of the ongoing advances in AI, but active shapers and owners of these technological advances.
This competition is open to all participants of the Ghana Data Science Summit (IndabaXGhana 2021), organized by Data Science Network in collaboration with Deep Learning Indaba. To join, contact the IndabaX Ghana organizers (info@indabaxghana.com).
Teams and collaboration
You may participate in competitions as an individual or in a team of up to four people. When creating a team, the team must have a total submission count less than or equal to the maximum allowable submissions as of the formation date. A team will be allowed the maximum number of submissions for the competition, minus the total number of submissions among team members at team formation. Prizes are transferred only to the individual players or to the team leader.
Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be immediately disqualified from the platform.
Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).
The Zindi user who sets up a team is the default Team Leader. The Team Leader can invite other data scientists to their team. Invited data scientists can accept or reject invitations. Until a second data scientist accepts an invitation to join a team, the data scientist who initiated a team remains an individual on the leaderboard. No additional members may be added to teams within the final 5 days of the competition or the last hour of a hackathon, unless otherwise stated in the competition rules
A team can be disbanded if it has not yet made a submission. Once a submission is made individual members cannot leave the team.
All members in the team receive points associated with their ranking in the competition and there is no split or division of the points between team members.
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 30 submissions per day.
You may make a maximum of 150 submissions for this 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 50% 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 50% 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.
You may only win prize money if you are residing in Ghana.
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
Data standards:
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions
This challenge was designed by AI community FUTA, Specifically for AI community FUTA Monthly Competition, which takes place 23-28 May. Welcome to the AI Community participants!
Teams and collaboration
You may participate in competitions as an individual.
Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. 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.
You may use pretrained models as long as they are openly available to everyone.
You are allowed to access, use and share competition data for any commercial,. 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 10 submissions per day.
You may make a maximum of 220 submissions for this 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 50% 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 50% 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
Data standards:
Consequences of breaking any rules of the competition or submission guidelines:
Monitoring of submissions
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 target
WGZRIT9 0
UOFLGFN 0
8F9K7D9 1
This competition is only open to participants of this year's Ghana Data Science Summit (IndabaX Ghana). Only Ghanaians residing in Ghana will be eligible for the Hackathon prizes.
1st Prize: 2000 cedis plus mentorship from Google
2nd Prize: 1500 cedis plus mentorship from Maverick Research and Wave-2 Analytics
3rd Prize: 1000 cedis and mentorship from Superfluid Labs
This hackathon will run from 1 July to 15 July 2021.
Competition closes on 15 July 2021.
Final submissions must be received by 15:30 PM GMT.
We reserve the right to update the contest timeline if necessary.
Join the largest network for
data scientists and AI builders