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Machine Learning Basics

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Event description

Are you interested in machine learning, but not sure where to start? Join us for this session with an AWS expert and demystify the basics. Using real-world examples, you’ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can unlock new insights and value for your business using machine learning. 

  • Level: Fundamental 

  • Duration: 1.30 hours 

Key topics covered

During this event, you will learn: 

  • What is Machine Learning? 

  • What is the machine learning pipeline, and what are its phases? 

  • What is the difference between supervised and unsupervised learning? 

  • What is reinforcement learning? 

  • What is deep learning? 

Intended audience

This event is intended for: 

  • Developers 

  • Solution architects 

  • Data engineers 

  • Individuals interested in building solutions with machine learning - no machine learning experience required!

Recommended follow-up training and resources

We recommend that attendees of this event continue learning with these: 

  • Courses 

  • Resources 

Registration is mandatory so please submit your details to secure your place at the event.

Event outline

Section 1: Machine learning basics  

  • Classical programming vs. machine learning approach 

  • What is a model? 

  • Algorithm features, weights, and outputs 

  • Machine learning algorithm categories 

  • Supervised algorithms 

  • Unsupervised algorithms 

  • Reinforcement learning 

Section 2: What is deep learning? 

  • How does deep learning work? 

  • How deep learning is different 

Section 3: The Machine Learning Pipeline 

  • Overview 

  • Business problem  

  • Data collection and integration 

  • Data processing and visualization 

  • Feature engineering 

  • Model training and tuning 

  • Model evaluation 

  • Model deployment 

Section 4: What are my next steps? 

  • Resources to continue learning

East African Time Zone: 10a.m to 11:30 p.m
West African Time ZONE: 12p.m to 1:30 p.m



Registration is mandatory so please submit your details to secure your place at the event.

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