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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?

Recommended follow-up training and resources

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

  • Courses

    • Deep Learning on AWS

    • MLOps Engineering on AWS

    • Practical Data Science with Amazon SageMaker

    • The Machine Learning Pipeline on AWS

  • Resources

  1. AWS Ramp-Up Guide: Machine Learning

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

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!

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

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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