This document discusses using Java and Graal VM to deploy machine learning services. It begins with introductions to AI, machine learning, and deep learning. It then discusses the most commonly used languages and frameworks for machine learning like Python, R, TensorFlow, Keras, etc. It also discusses how models are typically deployed in production using model serving frameworks. The document concludes by demonstrating how Graal VM can be used to deploy machine learning models in a Java environment, allowing models to be easily served as microservices.

1. Java and Graal VM to easily deploy
your machine learning services
Philippe Gottfrois - Pierre Paci - InTech SA

2. Philippe Gottfrois - Software engineer
focus on machine learning @Intech
Pierre Paci - Software engineer / Deep
learning engineer @Intech
twitter: @pierre_paci
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3. 1. Introduction
What is AI, machine learning and deep learning
2. The machine learning ecosystem
Languages, frameworks commonly used and how deployed in
production
3. Graal VM for deploy ML
Theory + Demo
3

4. 1. Introduction
What is AI, machine learning and deep
learning
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5. Machine learning and Artificial Intelligence
AI
Deep learning
Machine learning
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6. Machine learning
Supervised
Unsupervised
Reinforcement
Machine learning
- Labeled datas
- Find mapping
between given
inputs and outputs
- Predict output for
new inputs
- Unlabeled datas
- Find structure of the
datas
- Actions on an environment,
rewarded or not
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7. Machine learning applications
Mactores website -
https://www.mactores.com/services/aws-big-da
ta-machine-learning-cognitive-services/

8. Deep learning
8
Neuron schematic originally taken from
the US Federal public domain (Nerve
Tissue, retrieved March 2007)

9. Deep learning
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Input layer
Hidden layer
Output layer
Input 2
Input 1
Input 3
Output 1
Output 2

10. Features extraction + classification
Deep learning vs Machine learning - Is that a bike ?
Deep learning
Machine learning
Input
Input Features extraction Classification
Output
Output
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11. Machine learning process
Get raw datas
Clean and
select data
Select and
build a model
Predict Inference
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12. Machine learning process - Detect cancerous moles
Get raw datas
Clean and
select data
Select and
build a model
Predict Inference
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13. Which tools for machine learning ?
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14. 1. Introduction
What is AI, machine learning and deep learning
2. The machine learning ecosystem
Languages, frameworks commonly used and how deployed in
production
3. Graal VM for deploy ML
Theory + Demo
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15. 2. Graal VM for deploy ML
Languages, frameworks commonly used and
how deployed in production
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16. Machine learning languages use rate in Kaggle survey (2017)
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76 %
69 %
19 %
18 %
18 %
less than 5 %

17. Deep learning frameworks
100 371
29 647
8 947
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18. Deploy machine learning in production
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Model serving (frameworks based) Custom server
+

19. And in a Java environment ?
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20. 1. Introduction
What is AI, machine learning and deep learning
2. The machine learning ecosystem
Languages, frameworks commonly used and how deployed in
production
3. Graal VM for deploy ML
Live code
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21. 3. Graal VM for deploy ML
Live code
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22. Thanks !
Philippe Gottfrois - Pierre Paci - InTech
Any questions ?