Masterclass Machine Learning (Ronald Kleijn)

Machine Learning
Ronald Kleijn
24th of November 2017
#sitNL Master Class

Agenda
1. Intro to Machine Learning ( ~ 20 min)
2. Intro to Neural Networks and Deep Learning (~ 60 min)
3. Break (~ 10 min)
4. ML@SAP (~ 30 min)
5. TensorFlow (~ 60 min)

In case you thought you could relax…

6EXTERNAL© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Machine learning is the reality behind artificial intelligence
§ Big Data (for example, business networks,
cloud applications, the Internet of Things,
and SAP S/4HANA)
§ Massive improvements in hardware
(graphics processing unit [GPU] and
multicore)
§ Deep learning algorithms
§ Computers learn from data without
being explicitly programmed.
§ Machines can see, read, listen,
understand, and interact.
What is machine learning?
Why now?

General Machine Learning Process

Train, validate and test

Data set

Train, validate and test

Nope,
you still can’t relax…

Deep Learning Positioning

Intro to Neural Networks
and Deep Learning

Neural Network Example

Neural Network

Neural Network – Learning process

Different Type of Neural Network Architectures

Exercise Neural Network
Teachable Machine
Short url: https://goo.gl/DtWUcR
Long url: https://teachablemachine.withgoogle.com/

What is Deep Learning

Why Deep Learning

When to use Deep Learning

When not to use Deep Learning

Little decision flow to guide you when to use deep learning…

Common Deep Learning Terminology
1. Hidden Layers
Ÿ The self learning grouped neurons which job is to transform input to
something the output can use.
2. Neurons (or nodes) in a hidden layer
Ÿ Calculates a weighted sum of its inputs and adds a bias plus decides
whether it should be ”fired”
3. Weight
Ÿ Defines the strength of the connection between 2 nodes
4. Features
Ÿ What you feed into the network. For example weight, height if you would like
to identify a man or woman in a dataset.
5. Epoch
Ÿ A complete run over the dataset.

Exercise Deep Neural Network
Neural Network Playground
Short url: https://goo.gl/T44G42
Long url: http://playground.tensorflow.org/additionalprops
For additional properties:
Short url: https://goo.gl/4sYKGB
Long url: http://playground.tensorflow.org/

Now you can relax…

SAP needs to make the leap to become the Intelligent Enterprise
Transactional Enterprise Digital Enterprise Intelligent Enterprise
Maturity
Impact
§ Enterprise software
guides processes
§ Programmed/rule based
§ Human knowledge work
§ First autonomous
process steps with ML
§ Learning from single
customer data sets
§ End-to-end processes
require human-in-loop
with some predictive
support
2017
§ End-to-end AI drives core
business & support functions
§ Highly personalized by
business & user context
§ Humans focus on exceptions
and higher value work
2020
Yesterday

SAP Leonardo Digital Innovation System
Design
Thinking
Services
SAP Leonardo
Technologies
SAP Cloud Platform Microservices Open APIs Flexible Runtimes Integration
Multi-Cloud Infrastructure SAP Data Center Microsoft Azure
Machine
Learning
Blockchain
Big Data
Internet of
Things
Analytics
Data
Intelligence
Solution Ideation
& Vision
Rapid
Prototyping
Business Case
Development
Technology
Blueprint

SAP Leonardo Machine Learning enables the intelligent enterprise
76% of the world’s
transaction revenue
25 industries
12 lines of business
The world’s largest
business network
Data
Science
Platform
Intelligent Apps
Intelligent
Services
In-Database
ML
SAP Leonardo
Machine Learning & Conversational AI
Re-imagine business
processes with digital
intelligence
Increased customer
satisfaction with
superior service
Increase revenue with
superior sales targeting
and execution
Improving quality time
at work for employees
Enabling product,
process & business
model innovations
Business Outcomes

SAP Leonardo Machine Learning Foundation
Enabling customers and partners to build the intelligent enterprise
Applications
Ready to use
Training
Inference
SAP Leonardo Machine Learning Foundation
Ready to use Services
Bring your own Model
Customize Model
Create Training
SAP Cloud Platform

Ready-to-use Services: Easy Consumption
Calling REST APIS through the API Business Hub

Combine Machine Learning services
Broken product similarity search use case
Images DB
Image Feature
Extraction Service
Vectors DB
Image Feature
Extraction Service
Similarity Scoring
Result

Exercise ML@SAP
Excersize 1: Image Classification
Short url: https://goo.gl/tEgVqM
Long url: https://www.sap.com/developer/tutorials/ml-
fs-api-hub-image.html
Excersize 2: Topic Detection
Short url: https://goo.gl/GPXRqs
Long url: https://www.sap.com/developer/tutorials/ml-
fs-api-hub-text.html
Direct link to the API:
Short url: https://goo.gl/6SpDxm
If you do not have an s-number then you can use
one of the following users:
Username: connecttoinnovate<number>@grr.la
Example: connecttoinnovate01@grr.la
Password: Abcd1234!

SAP Leonardo Machine Learning Strategic Partnerships
§ Study & formulate best practices on AI tech,
§ Advance the public’s understanding of AI,
§ Serve as an open platform for discussion
and engagement about AI,
§ and its influences on people and society
§ SAP accepted as partner
§ Enables one global answer
to ML & AI ethics
§ SAP ML in Nvidia CEO Keynote
§ Access to latest pre-release
hardware (e.g. DGX station)
§ Open-source software library for
Machine Intelligence
§ Our standard ML framework
(ease of training, enablement)
Partners Focus Areas Achievements

ML Frameworks

Introduction

TensorFlow Fun 1

TensorFlow Architecture

Exercise TensorFlow Fun 2
Short url: https://goo.gl/Aks8yy
Long url: https://magenta.tensorflow.org/assets/sketch_rnn_demo/index.html

How does it work?

TensorFlow Fun 3

1. Hidden Layers
Ÿ The self learning grouped neurons which job is to transform input to
something the output can use.
2. Neurons (or nodes) in a hidden layer
Ÿ Calculates a weighted sum of its inputs and adds a bias plus decides
whether it should be ”fired”
3. Weight
Ÿ Defines the strength of the connection between 2 nodes
4. Features
Ÿ What you feed into the network. For example weight, height if you would like
to identify a man or woman in a dataset.
5. Epoch
Ÿ A complete run over the dataset.

1. Bias
Ÿ Influence what elements are more likely to occur defined outside of the input
data.
2. Label
Ÿ Identifying what the input should be.
3. Loss (or error)
Ÿ Whether or not the model has predicted to outcome correctly or not based
on data point, prediction and label, so the lower the loss the better!
4. Backpropagation
Ÿ The process of adjusting your variables (generally weight and bias) to
reduce loss

First, let’s install
TensorFlow
(native pip please)
Short url: https://goo.gl/jww1LE
Long url: https://www.tensorflow.org/install/

Exercise TensorFlow
Short url: https://goo.gl/yMU3pi
Long url: https://www.tensorflow.org/get_started/mnist/beginners

Links and Further Information
Official Website
Explore SAP Leonardo ML under http://www.sap.com/ml
• Watch the intro video
• Download the solution brief
• Read about the intelligent enterprise
• Learn about our Machine Learning foundation
Education
Participate in the openSAP course Enterprise Machine Learning in a Nutshell:
https://open.sap.com/courses/ml1 (overview course)
This masterclass was mainly based on the following openSAP deep-dive course
Enterprise Deep Learning with TensorFlow: https://open.sap.com/courses/ml2
Additional info
TensorFlow site
Deeplearn.js, a web based machine learning library for the web
AI Experiments with google

Thank you.

Masterclass Machine Learning (Ronald Kleijn)

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