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

Amazon Machine Learning Key Concepts

Data Sources

ML Models

Evaluations

Batch Prediction

Real-time Predictio

Accessing AML

Amazon ML Console

AWS CLI

Amazon ML API

AWS SDKs

Building a Machine Learning Application

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

Creating and Using Datasources

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

Training ML Models

Types of ML Models

Training Process

Training Parameters

Creating an ML Model

Data Transformation for Machine Learning

Importance of Feature Transformation

Feature Transformations with Data Recipes

Recipe Format Reference

Suggested Recipes

Data Transformations Reference

Data Rearrangement

Evaluating ML Models

ML Model Insights

Binary Model Insights

Multiclass Model Insights

Regression Model Insights

Cross-validation

Evaluation Alerts

Generating and Interpreting Predictions

Creating a Batch Prediction

Reviewing Batch Prediction

Reading the Batch Prediction

Requesting Real-time Predictions

Managing AML Objects

Listing Objects

Retrieving Object Descriptions

Updating Objects

Deleting Objects

Using AML to Predict Response to a Marketing Offer

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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