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LinkedIn Learning

AWS Machine Learning by Example

via LinkedIn Learning

Overview

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Take a deeper dive into machine learning with Amazon Web Services (AWS). Learn how to approach common machine learning tasks using key techniques.

Syllabus

Introduction
  • Welcome
  • Amazon ML and SageMaker
  • What you should know before watching this course
  • Setting up an AWS account
1. Introduction to Machine Learning
  • Machine learning overview
  • Learning algorithms and hyperparameters
  • Steps in AWS machine learning
2. Binary Model
  • Exploring our binary model data set
  • Preparing our data for AWS
  • Creating a datasource
  • Confirming AWS machine learning schema
  • Creating a binary classification model
  • Understanding binary model's predictive performance
  • Setting binary model's predictive performance
  • Using the binary classification model to generate predictions
  • Creating batch predictions in AWS machine learning
  • Binary classification model environment cleanup
3. Multiclass Model
  • Exploring our multiclass model data set
  • Multiclass data preparation
  • AWS multiclass machine learning model
  • Predictions and evaluations of multiclass learning model
  • Generate predictions for AWS multiclass
  • Creating multiclass batch predictions
  • Interpreting batch predictions
  • Clean multiclass model environment
4. Regression Model
  • Exploring our regression model data set
  • Regression data preparation
  • Creation of an AWS machine learning model
  • Predictions and evaluations of a machine learning model
  • Regression batch predictions
  • Clean regression model environment
5. Overview of Other AWS Capabilities
  • SageMaker, Deep Learning AMI, Apache MXNet
Conclusion
  • Next steps

Taught by

Jonathan Fernandes

Reviews

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