Indaba𝕏Kenya

The Nairobi Women in Machine Learning community is honoured to be hosting the first Indaba𝕏 in Kenya on 7th April, 2018 in partnership with the Busara Centre for Behavioural Economics.

Deep Learning Indaba

The Deep Learning Indaba was formed one year ago, with a mission to strengthen African machine learning. The first Indaba was held in September 2017, and saw the creation of a new community, one united by a shared commitment to science and learning, and the potential it has to transform our societies for the better.

The Deep Learning Indaba has two principal aims: to increase African participation and contribution to the advances in artificial intelligence and machine learning, and address issues of diversity in these fields of science. The Deep Learning Indaba 2018 will happen from 9 -15 September in Stellenbosch, South Africa and in Nairobi, Kenya in 2019.

About Indaba𝕏Kenya

A deep learning Indaba𝕏 is a locally-organised, one-day Indaba that helps spread knowledge and builds capacity in machine learning.

Indaba𝕏Kenya

Indaba𝕏Kenya will provide a host of excellent sessions led by Artificial Intelligence experts in Kenya as well practical and poster sessions as highlighted below:

Indaba𝕏Kenya Programme:

08:00am –08:30am : Arrival and Registration

08:30am -09:15am : Keynote: The ML Roadmap for Kenya: Where We Are And Where We Are Heading

09:15 am –11:00am : Practical Session: Learning Entity Embeddings of Categorical Variables

11:00 am–11:30am : Tea Break

11:30 am–13:00pm : Panel Session: Artificial Intelligence: Drivers and Forces at Play

13:00 pm –14:30pm: Lunch

1430 pm -1600pm : Poster Session

1700 pm –1800pm : Networking Cocktail

The Indaba𝕏Kenya Keynote — The ML Roadmap for Kenya: Where We Are And Where We Are Heading by Nikhil Ravichandar, Engagement Director Busara Centre for Behavioural Economics

Artificial Intelligence (AI) and related technologies have started to shape important parts of the digital economy and affect core areas of our increasingly networked societies. Whether transportation or manufacturing, social justice or health and education, AI has the potential to deeply impact our lives and shape our individual and collective futures in ways both visible and hidden.

The Keynote will focus on:

• where we are and how we got here
• where we are going in terms of data availability, priority areas for modelling, and the nature of collaboration (with some examples from Busara case studies)
• how do we navigate this space?

The Indaba𝕏Kenya panel session — Artificial Intelligence: Drivers and Forces at Play

Moderator: Proff. Bitange Ndemo, Associate Professor of Entrepreneurship and Innovation at the University of Nairobi’s Business School.

Panelists: Jessica Francisca Colaço, Ciira Maina, Chris Orwa, Alex Gakuru and Kendi Muchungi

When considering the role of AI and how it shapes our individual lives and the future of society at large, the importance of data becomes visible very quickly. This panel discussion will attempt to broaden the perspective from a focus on just the data to additional key drivers and forces that shape AI, in general and with a particular focus on inclusion.

These forces include:

• User/Behavioural expectations
• Algorithms and Design
• Data and Infrastructure
• Business Models
• Law and Governance

The Indaba𝕏Kenya Practical Session — Learning Entity Embeddings of Categorical Variables

The problem: Many companies that have been using the internet, or digital technologies for multiple years, have rows and rows of data in database tables or spreadsheets. For example, a supermarket with citywide reach and multiple branches will have data that records, or may at least help to infer, the number of sales in each store. As part of a growth strategy, it would probably help to know what to expect of future sales given historical trends. There are many reasons for this, including:

1. Effective staff scheduling increases motivation and productivity. It is better to know how many people to have on staff if there will be a spike in sales before a public holiday, for example.
2. Effective inventory management reduces the likelihood that products people need get bought from somewhere else, because they ran out of nearby stores.

Using this example, we need to learn, from the data, to predict future sales. Various methods can be employed to solve this problem, each with varying requirements for domain knowledge (expertise in the drug store business and logistics), and statistical skill. What we’ll study in the practical session is one winning method, based on deep learning, with minimal feature engineering, aka very little domain expertise. It is a copy of the third-place solution in the Kaggle competition ‘Rossmann Store Sales’, and its main goal is to teach the idea of entity embeddings of categorical variables. Participants will learn what categorical variables are, how to recognize them, and how to build, use and learn from embedding matrices of them. The only prerequisite for participating is Python experience. All of the matrix math and neural networks knowledge will be introduced during the talk led by Brian Muhia, Amina Islam and Kathleen S.

Indaba𝕏Kenya Poster Sessions

The poster session will provide an informal forum to showcase innovative projects and research that includes the use of Artificial Intelligence​. Posters may include narratives, tables, graphs, and handouts.

Indaba𝕏Kenya Partners

The 2018 Indaba𝕏Kenya is made possible through a partnership with Nairobi WiMLDS, Deep Learning Indaba and the Busara Centre for Behavioral Economics.

Are you interested in attending Indaba𝕏Kenya? Be sure to submit your application here.Applications will be open from March 2nd to March 16th.

Applications now open: Deep Learning Indaba Kambule and Maathai Awards

PS: Applications for the Kambule and Maathai Awards are now open and will award Excellence in African Machine Learning.

The Kambule doctoral dissertation award and the Maathai impact award will be conferred annually at the Deep Learning Indaba, and form part of our broader mission to strengthen African machine learning. These awards recognise ability, struggle, effort, and African excellence. But importantly, the award winners will serve as an inspiration to our broader community — like the inspiration we gain from the illustrious Africans after whom these awards are named — allowing us to recognise the ability that we ourselves have to make meaningful contributions to our societies. These awards will tell the story of African AI innovation, and we hope that you will celebrate the excellence of those you know by nominating them for these awards. For full details see deeplearningindaba.com/awards.