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AI & Machine Learning | System Architecture
October 31, 2017 @ 5:30 pm - 8:00 pm
Join us at Outbox on Tuesday 31st October 2017 from 5:30 pm to 8:00 pm as we share ideas on the following topics.
Session 1: 1 Hour
Artificial Intelligence & Machine Learning: Convolutional Neural networks for computer vision.
We live in an interesting period when technology has finally evolved to solve algorithms that were initially published over 50 years ago – Artificial neural networks (ANNs). These are nature inspired algorithms greatly used in the field of artificial intelligence, more specifically a branch called deep learning. Deep learning is a technique used to develop applications considered intelligent covering a wide range including but not limited to:
Recommender systemsSpeech and writing pattern classification, Face recognition with computer vision, Control of high speed trainsStocks forecasting on financial markets, Anomaly detection on medical images, Control of electronic devices, washing machines, ovens etc.
What we shall cover?
1) An intuitive overview of machine learning, neural networks and deep learning
2) Architecture of neural networks
3) Convolutional neural networks, what they are and how they work
4) How to build your own neural network
5) How we are using deep learning at the AI lab Makerere university
6) Other creative use-cases of deep learning
Who should attend?
Developers/Researchers curious about artificial intelligence/machine learning/deep learning especially in the field of computer vision.
A basic understanding of programming concepts is required, especially in python.
Entrepreneurs/Business people willing to learn how machine learning can be used to improve marketing.
Anyone curious about deep learning.
At the end of this training, the black-box that is machine learning, neural networks and deep learning will hopefully be demystified, and you shall have a general intuitive understanding on how artificial intelligence works under the hood.
Benjamin Akera; A Data scientist, software developer and research scholar at the Artificial Intelligence research lab, Makerere University, BSc. Software Engineering (MUK) enthusiastic about the applications of data science methods in the developing world.
Session 2: 1 Hour
System Architecture: System Architecture that serves at scale, a case for microservices
System Architecture is one of the most over looked sections of software development. We shall look at best practices when building applications for scale.
What shall we cover?
Decoupling Mononolith Applications into Micro services top serve at scale. We shall make the case for Micro services architecture and how to go about building one for existing applications or applications starting from scratch.
Who should attend?
Software developers interested in building applications that will serve high traffic.
Best practices when designing applications that are resilient and scalable
Facilitator Alex Nyika Omuyonga: A Senior Software Developer Laboremus Uganda Limited. Alex started his development career in Nairobi where he worked for a Fintech Company. He returned to Uganda to Work for MTN Uganda where he was part of teams that built high traffic applications that served MTN’s customers. Presently he is part of a team that builds and maintains fintech applications targeted for the Norwegian Market.