Join Jonathan Fernandes for an in-depth discussion in this video Next steps, part of AWS Machine Learning by Example.
- [Jonathan] I've really enjoyed putting together…this AWS Machine Learning course.…What can you do with what you've learned on this course?…Both Kaggle and the Machine Learning Repository…at the University of Irvine have several data sets.…I encourage you to pick a data set,…figure out if any of the three techniques…we've looked at would help you make any predictions,…and then try it out on the AWS Machine Learning service.…You can also try and improve on some…of the predictions by experimenting…with the hyper parameters available…when you create a custom machine learning model.…
I hope you've found this course useful,…I'd love to hear back from you.…You're welcome to connect via LinkedIn.…
Author
Jonathan Fernandes
Updated
9/24/2019Released
4/25/2018- Learning algorithms and hyperparameters
- Preparing data for AWS
- Using binary, multiclass, and regression techniques
- Creating a datasource
- Generating predictions
- Creating and interpreting batch predictions
- Additional AWS capabilities
Skill Level Intermediate
Duration
Views
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Introduction
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Welcome56s
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Amazon ML and SageMaker2m 15s
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Setting up an AWS account1m 49s
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1. Introduction to Machine Learning
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Machine learning overview1m 34s
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2. Binary Model
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Preparing our data for AWS4m 48s
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Creating a datasource2m 25s
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3. Multiclass Model
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Multiclass data preparation4m 27s
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4. Regression Model
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Regression batch predictions2m 59s
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5. Overview of Other AWS Capabilities
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Conclusion
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Next steps39s
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Video: Next steps