AWS DISCOVERY DAY: MACHINE LEARNING BASICS
- Code training GKAWS-MLB
- Duur 1 dag
Andere trainingsmethoden
Ga naar:
Methode
Deze training is in de volgende formats beschikbaar:
-
Klassikale training
Klassikaal leren
-
Virtueel leren
Virtueel leren
Vraag deze training aan in een andere lesvorm.
Trainingsbeschrijving
Naar bovenLearn about important concepts, terminology, and the phases of a machine learning pipeline.
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
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
Data
Naar bovenDoelgroep
Naar bovenThis event is intended for:
- Developers
- Solution architects
- Data engineers
- Individuals interested in building solutions with machine learning - no machine learning experience required!
Trainingsdoelstellingen
Naar bovenDuring 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?
Inhoud training
Naar bovenSection 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
Vervolgtrainingen
Naar bovenCourses
- Deep Learning on AWS
- MLOps Engineering on AWS
- Practical Data Science with Amazon SageMaker
- The Machine Learning Pipeline on AWS
Resources
- AWS Ramp-Up Guide: Machine Learning
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