amazon machine learning im einsatz: smartes marketing - aws machine learning web day

Targeted Marketing with Amazon Machine Learning

Barbara Pogorzelska,

Technical Program Manager

Agenda

• Problem description

• Downloading, editing and uploading the data

• Datasource creation

• ML model creation

• Model evaluation

• Batch prediction

• Clean up

Problem Description

Machine learning & the use case

Machine learning is the technology that automatically finds

patterns in your data and uses them to make predictions for

new data points as they become available

Problem

How to identify potential customers for targeted marketing

campaigns?

Data available

Publicly available banking and marketing dataset from the

University of California at Irvine (UCI) repository

Amazon Machine Learning tutorial

Amazon Machine Learning tutorial

Data (see http://archive.ics.uci.edu/ml/datasets/Bank+Marketing)

Training data

41188 data points

20 attributes

binary output

Batch predictions

4119 data points

Bank client data

1 - age 2 - job (admin., blue-collar, entrepreneur, …)3 - marital (single, divorces, married, …) 4 - education (basic.4y, basic.6y, university.degree, …)5 - default: has credit in default? 6 - housing: has housing loan?

7 - loan: has personal loan?

Related with the last contact of the current campaign

8 - contact: communication type: (cellular, telephone) 9 - month: last contact month of year10 - day_of_week: last contact day of the week 11 - duration: last contact duration, in seconds

Other attributes

12 - campaign: number of contacts performed during this

campaign and for this client

13 - pdays: number of days that passed by after the client

was last contacted from a previous campaign

14 - previous: number of contacts performed before this

campaign and for this client

15 - poutcome: outcome of the previous marketing

campaign

Social and economic context attributes

16 - emp.var.rate: employment variation rate

17 - cons.price.idx: consumer price index

18 - cons.conf.idx: consumer confidence index

19 - euribor3m: euribor 3 month rate - daily indicator

20 - nr.employed: number of employees

Output variable (desired target)

21 - y - has the client subscribed a term deposit?

Three steps to create a prediction

Downloading, editing and uploading the data

Storing the data on S3

• Download from https://s3.amazonaws.com/aml-sample-data/banking.csv and

https://s3.amazonaws.com/aml-sample-data/banking-batch.csv

– Replaced yes/no with 1/0

• Store data on S3

Datasource creation

Datasource creation

Datasource creation

Datasource creation

Datasource creation

Datasource creation

Three steps to create a prediction

ML model creation

Model creation – default model

Model creation – default model

Model creation – default model

Model creation – default model

Model evaluation

Model evaluation – default model

Model evaluation – default model

Model evaluation – default model

Data Insights

Data Insights

Data Insights

Data Insights

Data Insights

Data Insights

Model creation – custom model

Model creation – custom model

Model creation – custom model

Model creation – custom model

Three steps to create a prediction

Batch predictions

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - default model

Batch predictions - custom model

Batch predictions - custom model

Batch predictions - custom model

Batch predictions - custom model

Clean up

Clean up your account

To delete the input data used for training, evaluation, and batch prediction steps

1. Open the Amazon S3 console.

2. Navigate to the S3 bucket where you stored the banking.csv and banking-batch.csv.

3. Select the two files and the .writePermissionCheck.tmp file.

4. Choose Actions, Delete.

5. When prompted for confirmation, choose OK.

To delete the predictions generated from the batch prediction step

1. Open the Amazon S3 console.

2. Navigate to the bucket where you stored the output of the batch predictions.

3. Select the batch-prediction folder.

4. Choose Actions, Delete.

5. When prompted for confirmation, click OK.

Try out machine-learning-samples from github

https://aws.amazon.com/de/machine-learning/

Get Started on AWS with

Amazon Machine Learning