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Machine Learning Basics

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: 1.5 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

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!
 

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

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

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

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