Duration

1 days.

Prerequisites

  • Familiarity with Python programming language
  • Basic understanding of Machine Learning

Skills Gained

  • Prepare a dataset for training
  • Train and evaluate a Machine Learning model
  • Automatically tune a Machine Learning model
  • Prepare a Machine Learning model for production
  • Think critically about Machine Learning model results

Who Can Benefit?

  • Developers
  • Data Scientists

Outline for Practical Data Science with Amazon SageMaker Training

Module 1: Introduction to Machine Learning

  • Types of ML
  • Job Roles in ML
  • Steps in the ML pipeline

Module 2: Introduction to Data Prep and SageMaker

  • Training and Test dataset defined
  • Introduction to SageMaker
  • Demo: SageMaker console
  • Demo: Launching a Jupyter notebook

Module 3: Problem formulation and Dataset Preparation

  • Business Challenge: Customer churn
  • Review Customer churn dataset

Module 4: Data Analysis and Visualization

  • Demo: Loading and Visualizing your dataset
  • Exercise 1: Relating features to target variables
  • Exercise 2: Relationships between attributes
  • Demo: Cleaning the data

Module 5: Training and Evaluating a Model

  • Types of Algorithms
  • XGBoost and SageMaker
  • Demo 5: Training the data
  • Exercise 3: Finishing the Estimator definition
  • Exercise 4: Setting hyperparameters
  • Exercise 5: Deploying the model
  • Demo: Hyperparameter tuning with SageMaker
  • Demo: Evaluating Model Performance

Module 6: Automatically Tune a Model

  • Automatic hyperparameter tuning with SageMaker
  • Exercises 6-9: Tuning Jobs

Module 7: Deployment / Production Readiness

  • Deploying a model to an endpoint
  • A/B deployment for testing
  • Auto Scaling Scaling
  • Demo: Configure and Test Autoscaling
  • Demo: Check Hyperparameter tuning job
  • Demo: AWS Autoscaling
  • Exercise 10-11: Set up AWS Autoscaling

Module 8: Relative Cost of Errors

  • Cost of various error types
  • Demo: Binary classification cutoff

Module 9: Amazon SageMaker architecture and features

  • Accessing Amazon SageMaker notebooks in a VPC
  • Amazon SageMaker batch transforms
  • Amazon SageMaker Ground Truth
  • Amazon SageMaker Neo
12/18/2023 - 12/18/2023
09:00 AM - 05:00 PM
Eastern Standard Time
Online Virtual Class
USD $745.00
Enroll
02/02/2024 - 02/02/2024
12:00 PM - 08:00 PM
Eastern Standard Time
Online Virtual Class
USD $745.00
Enroll
03/22/2024 - 03/22/2024
09:00 AM - 05:00 PM
Eastern Standard Time
Online Virtual Class
USD $745.00
Enroll