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Amazon Machine Learning (AML) for Developers Training

Live Online & Classroom Enterprise Training

Master the core concepts - data source, ML models, evaluation, batch and real-time predictions of Amazon Machine Learning. Learn hands-on to use APIs to integrate your ML models with your application.

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What is Amazon Machine Learning Training about?

Master the tools and wizards to create robust ML models on Amazon Cloud. Obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure. In the cloud, labs practice making live application to predict the response to a marketing offer. Be industry-ready to develop cutting-edge intelligent apps in the fastest possible time with our AML training.

Suggested Audience

Developers with any amount of experience with or without a data science background wanting to develop an intelligent application in a short span of time

What are the objectives of Amazon Machine Learning Training ?

This Amazon Machine Learning course enables you to:

  • Gain an in-depth understanding of key concepts of Amazon Machine Learning (AML)
  • Integrate machine learning with your app with minimal effort Explore data sources and manipulate data within AML
  • Build, train, evaluate and improve your models without having to understand infrastructure deployment issues
  • Generate and integrate real-time predictions to help you develop an intelligent application that your organization needs

What are the prerequisites for Amazon Machine Learning Training?

Required: Development experience in any programming language

Suggested: Knowledge of AWS

Duration: 2 Days

Available Training Modes

Live Online Training

18 Hours

Classroom Training

3 Days

Course Outline Expand All

Expand All

  • Data Sources
  • ML Models
  • Evaluations
  • Batch Prediction
  • Real-time Predictio
  • Amazon ML Console
  • AWS CLI
  • Amazon ML API
  • AWS SDKs
  • Formulating the Problem
  • Collecting Labeled Data
  • Analyzing your Data
  • Feature Processing
  • Splitting the data into Training and Evaluation Data
  • Training the Model
  • Linear Models
  • Learning Algorithms
  • Training Parameters
  • Evaluating Model Accuracy
  • Improving Model Accuracy
  • Using the Model to Make Predictions
  • Retraining Models on New Data
  • Understanding the data format for AML
  • Creating a Data Schema for AML
  • Splitting Your Data
  • Data Insights
  • Using Amazon S3 with Amazon ML
  • Creating an Amazon ML Datasources from Data in Amazon Redshift
  • Using Data from an Amazon RDS Database to Create and AML Datasource
  • Types of ML Models
  • Training Process
  • Training Parameters
  • Creating an ML Model
  • Importance of Feature Transformation
  • Feature Transformations with Data Recipes
  • Recipe Format Reference
  • Suggested Recipes
  • Data Transformations Reference
  • Data Rearrangement
  • ML Model Insights
  • Binary Model Insights
  • Multiclass Model Insights
  • Regression Model Insights
  • Cross-validation
  • Evaluation Alerts
  • Creating a Batch Prediction
  • Reviewing Batch Prediction
  • Reading the Batch Prediction
  • Requesting Real-time Predictions
  • Listing Objects
  • Retrieving Object Descriptions
  • Updating Objects
  • Deleting Objects
  • Prepare your data
  • Create a Training Datasource
  • Create an ML Model
  • Review ML Model's Predictive Performance
  • Generate Predictions
  • Clean Up

Who is the instructor for this training?

The trainer for this Amazon Machine Learning (AML) for Developers Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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