Attending the Deep Learning Indaba Summer School: My Personal Experience
Last year I applied to the Deep Learning Indaba 2017 summer school, and never in million years would I ever have imagined that it would lead to all it did.
From the first interaction at the registration, you feel at ease when you are warmly welcomed by the Indaba organizing committee who, from my own personal experience, are the kindest people on earth. You won’t help but love them instantly.
The Indaba was more than well organized, the organizing committee payed attention to all the small details, from food options to the randomly assigned rooms for practical sessions by the big five game animals (so cool! ) to ensure a maximum of networking between students and tutors and make sure that everyone’s needs were taken care of. The schedule was meticulously set up to walk each participant slowly through the fundamentals of Machine Learning and Deep Learning, so that no matter what year or type of studies you are in (MSc, PhD, Postdoc) if you are a student, or even if you are an academic, engineer in data science, research scientist at startups or industry; you would be able to easily follow and benefit from the Deep Learning Indaba training.
The learning process was very thoughtful and efficient; the choice of order of the different topics facilitated the learning task. The alternation between theoretic and practical sessions ensured a maximum understanding of the topics. And the poster sessions were the best way to interact with fellow students and pick the brain of some of the smartest accomplished researchers out there.
In only one week, you get to learn more than you ever did about Machine Learning and Deep Learning from experts in the field. You get to meet and network with quality people from all over the world who share the same interests and passions you do about AI, and how it will change the world.
The organizers encouraged all the attendees to participate in the poster sessions, and there were so many prizes up for grabs for the best posters. 37 students were awarded various prizes: NVidia GPU awards, Cambridge University Press Prizes, MIT Press Prizes, plus the NIPS Travel Award which was revealed as a secret prize at the ending ceremony. I was very lucky to win both the NIPS Travel Award and the NVidia GPU Award. I am so grateful to all of those who made this possible for me. I got to go to America and attend one of the top Machine Learning conferences out there. And this wouldn’t have been possible without the Deep Learning Indaba.
Attending the Indaba was exactly what I needed to fill in the gaps in my knowledge about AI, it was the push I desperately was in need for to improve and finish some of the work I had going on, all thanks to the valuable and constructive suggestions of the mentors during my poster presentation. For me, the Indaba was that extra boost any graduate student would yearn for to regain the motivation which is hard to keep after so many years stressing out about the PhD. It can be a refreshing experience, as it can be a new start, since shortly afterwards I was offered some amazing opportunities: collaborations, internships and even job offers from giant tech companies.
Through the Indaba, I not only got to meet and talk with some AI celebrities I have been following on social media for a while now, I also got to befriend and learn directly from their experience both on a professional and personal level. The Indaba lecturers were more like mentors than regular scholars who give their talk and walk away. I think that the key difference here is that you can easily sense how committed they are to the cause, and how passionate they are about sharing and giving back to the African community.
As much as we would like to hide it, Africa keeps lagging behind in science and technology. Participations from African students and scientists are few to non-existent in top tier conferences. The only participations you would have from African people will be from those who were lucky enough to go finish their studies outside of the motherland. And this needs to change!
We, Africans, need to make the change happen! We need to do our best to “be the change we want to see in the world” as Gandhi said. The deep learning Indaba is the best starting point for anyone interested in doing that.
As Timnit Gebru co-founder of the Black in AI workshop said: “ There is a bias to what kinds of problems we think are important, what kinds of research we think are important, and where we think AI should go. If we don’t have diversity in our set of researchers, we are not going to address problems that are faced by the majority of people in the world. When problems don’t affect us, we don’t think they’re that important, and we might not even know what these problems are, because we’re not interacting with the people who are experiencing them.”
It is up to us, Africans, to help in the development of our continent. Strengthening African Machine Learning is one way to do it. Once we get a hold of the right tools, we can choose where AI and Machine Learning would go to address our own needs. Most of the problems an African would face wouldn’t even be taken into consideration by non-Africans. I am talking education, health, poverty… issues. And as a powerful science promising to change the world, AI needs to be included in our teachings, to form the next generation of problem solvers from Africa and to Africa.
Participating in the Deep Learning Indaba was for sure the best thing I ever did and I encourage everyone to do the same this year by applying here, so that we can all start doing our best to help strengthen African Machine Learning.
