Last week I commited to documenting my journey into the vast world of MLOps. My goal is to become well-versed in productionizing machine learning models at scale. As I write this article, I find myself at the Deep Learning Indaba, a conference that is dedicated to bringing together the African machine learning and AI community with the mission to strengthen African AI. We’re currently experiencing the excitement of Day 1. However, before getting into the details of the conference, let’s rewind to my preparations and learnings from the past week.
During the past week, I embarked on the “Data Science in Production” course offered by Educative as mentioned in my previous post. Here are some key topics I learnt from the introductory phase:
- Introduction to the course itself.
- Distinguishing between an applied and a product data scientist.
- Exploring some techniques for importing datasets that will be crucial for the remainder of the course.
- Setting up my cloud environment on AWS.
- Familiarising myself with the FeatureTools library, a powerful tool for automating feature engineering.
The past week presented its fair share of challenges. Setting up my cloud environment, preparing for the Deep Learning Indaba alongside wrapping up work commitments proved to be time-consuming and demanded a substantial portion of my time and energy. Nonetheless, we still made time to learn something and make some progress on the course! Whoop! 🙌
Deep Learning Indaba Highlights
Of course, a small portion of my week was taken up by the Deep Learning Indaba and therefore, let me share my highlights so far from the conference. It’s honestly been a whirlwind of knowledge and networking from the moment I landed in Ghana. I was really excited to meet people from the community that I haven’t seen in a long time! On Day 0, practical sessions were on the agenda, although I missed out because I was on transit to the event. Nevertheless, the evening brought an exciting opening party that set the stage for the days to come. Day 1 kicked off with a captivating keynote address by Dr. Ayokor Korsah, a distinguished Computer Science Lecturer at Ashesi University. The day continued with a diverse range of sessions and I had the privilege of attending a presentation on the African Startup Landscape, delivered by Pelonomi Moiloa, one of the founders of Lelapa AI. The afternoon was filled with practical sessions (you can find the practical sessions here), and as I write this, we’re about to wrap up the day with a keynote from the renowned Timnit Gebru, followed by a Women in Machine Learning and Data Science evening panel session and a delightful cocktail party which I’m looking forward to 😊.
In the coming week, my primary focus will be on absorbing as much knowledge as I can from the Deep Learning Indaba. I’m excited to share a more detailed article on my personal highlights from the conference next week. Until then, stay tuned for more updates on my journey into MLOps!
Till next time!