The explore series demo day

The Nairobi Women In Machine Learning and Data Science community is a group for women interested in Artificial Intelligence, Machine Learning, and Data Science. We meet to socialize and to discuss artificial intelligence, machine learning, and data science in an informal setting with the purpose of building a community around women in these fields. We usually meet on the third Saturday of each month.



In April we began a series named The Explore Series that is targeted on beginners in AI/ML/DS. In the third month of the explore series, we decided to do an event to showcase projects that the community members have been working on during this year.

In partnership with Andela and Alliance4ai, this event was successful and we got to learn a lot and network with the speakers about the projects they showcased.


We had an opening keynote from Mercy Orangi who is the Developer Relations Manager, Africa at Andela. Mercy gave a keynote about planning for growth in a career in tech. She talked about five key points to plan for career growth


  • Identify your goals by divergent thinking moonshot ideas and convergent thinking breaking down goals to short term, mid-term then long term goals.
  • Practice, Practice by doing internships, projects.
  • Getting a mentor
  • Sharing your work
  • Learn, unlearn and relearn


After the keynote, we began our project session whereby our first speakers Wambui Kuria, Sam Gitau, and Duncan did a presentation on Netflix viewership analysis. They took us through  Natural Language data processing and did the modeling of a recommendation system when you key in a movie you liked on Netflix it will recommend the other five movies that are similar.

The second presentation was done by Robert Ayub Odhiambo who is a Senior Officer Data Scientist at Safaricom PLC. He took us through the data pipeline of a Natural Language Processing(NLP)project and also went in-depth of explaining the different libraries used in NLP. Later on, he took us through code that he did on text classification of Swahili and English text and farther showed us what he is working on in the deployment of the model in a chatbot using chatyfy.

The third presentation was done by Stephanie Omwanda, Jasline Gati, and Maureen Mathenge who were doing analysis on COVID 19. The team was able to do visualizations on the recovering rate in comparison to the death rate. They also did a correlation between Covid19 and other viruses that seem to be in the coronavirus bracket such as SARS and Ebola. They used libraries such as ARIMA and Facebook Prophet to build a model that predicts the probability of getting infected, surviving, or dying from the coronavirus.

The fourth presentation was done by Eunice Mutahi and Brian who did a presentation on tweet sentiment analysis.    They trained an NLP model with the aim to determine if a tweet is positive, negative, or neutral with an objective to use it to improve customer satisfaction to manage the reputation of a company.

The fifth presentation was done by Wambui Kuria and Tom Njoroge

who did an analysis on Youtube and gave us amazing insights based on data up to 2019. They also did a hypothesis test with some visualizations that showed the best time to post a youtube video and get more views is on Friday at 4 pm when people are very active on youtube.

The final presentation was a simple reporting tool done by Faith Mwai a system analyst at KPLC. She explained with the growing rise of data usage, reporting has become an essential need for companies. Companies no longer want to just sit and wait to make decisions. They want to use data to enable them to come up with solutions ahead of time yet remain competitive in their areas. Reporting tools are expensive and some don’t fit into some aspects of every company. Therefore there is a need to have a way of getting the reports and visualizing them dependently on company data. She worked on a tool with an aim to address the issue of flexibility and scalability. It will ensure that you can customize a report real-time and enable decision making without having to wait for data clean up and storage.


About the Author

Rose Delilah Gesicho is a gregarious individual who geeks out about data. She has a background in Data Science and she is very passionate about Artificial Intelligence and community development. She is a program coordinator for the Nairobi Women In Machine Learning and Data Science. She aims to build a large community of data enthusiasts to help solve Africa’s problems using Artificial Intelligence.


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