Meet The Winners of Tourism Expenditure Prediction Challenge

Build a ML Model to predict Tourist Expenditure in Tanzania

Last week I organized a Tourism Machine Learning Hackathon called Tanzania Tourism Prediction Challenge hosted & supported by Zindi Africa and Tanzania Pycon Community during the Second Pycon conference here in Tanzania.

If you don’t know Zindi Africa, in short, Zindi Africa is Africa’s largest data science competition platform, solving complex challenges using artificial intelligence (AI) and machine learning (ML). The platform allows data scientists across the African continent to compete to solve challenges that focus on , to name a few.

Zindi Africa Photos

The Tanzania Pycon Conference is an annual gathering of Python programming language users in Tanzania which includes web developers, software developers, data scientists, data analysts, Ethical hackers, Researchers, IoT Engineers & techies from various organizations. The conference is organized by members of the Python Tanzania Users Group, a community dedicated to advancing the use of the Python language and technology in Tanzania. This annual gathering involves .

Pycon Conference 2020

Why Tanzania Tourism Sector?

The Tanzanian tourism sector plays a significant role in the Tanzanian economy, contributing about 17% of the country’s GDP and 25% of all foreign exchange revenues. The sector, which provides direct employment for more than 600,000 people and up to 2 million people indirectly, generated approximately $2.4 billion in 2018 according to government statistics. Tanzania received a record 1.1 million international visitor arrivals in 2014, mostly from .

Tanzania is the only country in the world that has allocated more than 25% of its total area for wildlife, national parks, and protected areas. There are

Tanzania’s tourist attractions include the Serengeti plains, which hosts the largest terrestrial mammal migration in the world; the Ngorongoro Crater, the world’s largest intact volcanic caldera and home to the highest density of big game in Africa; Kilimanjaro, Africa’s highest mountain; and the Mafia Island marine park; among many others. The scenery, topography, rich culture, and very friendly people provide for excellent cultural tourism, beach holidays, honeymooning, game hunting, historical and archaeological ventures, and certainly the best wildlife photography safaris in the world.

The objective of this hackathon is to develop a machine learning model to predict what a tourist will spend when visiting Tanzania. The model can be used by different tour operators and the Tanzania Tourism Board to automatically help tourists across the world estimate their expenditure before visiting Tanzania.

After running the hackathon for 3 days, the top 3 winners of this challenge are Daudi Nkanda from the University of Dar es salaam in 1st place, Anthony Mipawa from the University of Dodoma in 2nd place, and Frank E Anderson from the University of Agriculture in 3rd place.

A special thank you to the 1st, 2nd, and 3rd place winners for sharing some insights into how they succeeded in this challenge so we can learn from them.

1st Winner: Daudi Nkanda

Daudi Nkanda

Tell us a bit about yourself?

Tell us about the approach you took?

What were the things that made the difference for you that you think others can learn from?

What are the biggest areas of opportunity you see in AI in Tanzania over the next few years?

What are you looking forward to most about the Zindi community?

What are the biggest areas of opportunity you see in AI in Africa over the next few years?

2nd Winner: Anthony Mipawa

Anthony Mipawa

Tell us a bit about yourself?

Tell us about the approach you took?

What were the things that made the difference for you that you think others can learn from?

What are the biggest areas of opportunity you see in AI in Tanzania over the next few years?

What are you looking forward to most about the Zindi community?

What are the biggest areas of opportunity you see in AI in Africa over the next few years?

Second Winner

You can access Anthony’s notebook for this challenge here: 👇 https://github.com/Tonyloyt/TanzaniaTourism-Hackathon-2020-Second-place-Winning-Solution

You can follow Anthony on Twitter here 👉 https://twitter.com/loyttony to learn more from him.

3rd Winner: Frank E. Anderson

Frank E Anderson

Tell us a bit about yourself?

Tell us about the approach you took?

What were the things that made the difference for you that you think others can learn from?

What are the biggest areas of opportunity you see in AI in Tanzania over the next few years?

What are you looking forward to most about the Zindi community?

What are the biggest areas of opportunity you see in AI in Africa over the next few years?

Third Winner

You can access Frank’s notebook for this challenge here: https://gitlab.com/dashboard/projects

Resources for Tourism in Tanzania

Do you want to visit Tanzania and spend quality time at the different national parks, historical sites and meet beautiful people, here are good resources for you to learn more and know where you can start!.

Wrapping Up

Davis David (Zindi Ambassador)

I want to say thank you to Zindi Africa and Pycon Community to make this machine learning hackathon successful.

I would like to wish you a happy holiday season, as well as a wonderful New Year! 2021. Take advantage of this time to reconnect with your family & friends 👪 . May 2021 bring you health, happiness, and success!

Before you leave

Please share it so that others can see it. Feel free to leave a comment too. Till then, see you in the next post! I can also be reached on Twitter @Davis_McDavid.

Data Scientist | AI Practitioner | Software Developer. Giving talks, teaching, writing. Contact me to collaborate davisdavid179@gmail.com