Short Introduction to Python & Jupyter

Cloud Computing & Big Data

PARALLEL & SCALABLE MACHINE LEARNING & DEEP LEARNING

Prof. Dr. �C Ing. Morris Riedel

Associated Professor

School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland

Research Group Leader, Juelich Supercomputing Centre, Forschungszentrum Juelich, Germany

PRACTICAL LECTURE 0.1

Short Introduction to Python & Jupyter

September 3, 2020

Online Lecture

@Morris Riedel

@MorrisRiedel

@MorrisRiedel

Review of Lecture 0 �C Prologue

? Course Motivation & Information

? Course Organization & Content

[11] Jupyter

[1] big-data.tips [4] Keras

[2] NVIDIA [3] TensorFlow

Practical Lecture 0.1 �C Short Introduction to Python & Jupyter

[12] Python

[9] Apache Hadoop [10] Apache Spark

[5] Amazon Web Services [6] Microsoft Azure [7] Google Cloud [8] EOSC-Nordic

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Outline of the Course

1.

Cloud Computing & Big Data Introduction

11. Big Data Analytics & Cloud Data Mining

2.

Machine Learning Models in Clouds

12. Docker & Container Management

3.

Apache Spark for Cloud Applications

4.

Virtualization & Data Center Design

5.

Map-Reduce Computing Paradigm

6.

Deep Learning driven by Big Data

7.

Deep Learning Applications in Clouds

8.

Infrastructure-As-A-Service (IAAS)

9.

Platform-As-A-Service (PAAS)

10. Software-As-A-Service (SAAS)

Practical Lecture 0.1 �C Short Introduction to Python & Jupyter

13. OpenStack Cloud Operating System

14. Online Social Networking & Graph Databases

15. Big Data Streaming Tools & Applications

16. Epilogue

+ additional practical lectures & Webinars for our

hands-on assignments in context

? Practical Topics

? Theoretical / Conceptual Topics

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Outline

? Python Environments

?

?

?

?

?

Python Programming Language with NumPy & Pandas Libraries

Deep Learning with Tensorflow & Keras

Project Jupyter with JupyterLab and JupyterHub

Anaconda Distribution @ Local Laptop

Jupyter @ Juelich Supercomputing Centre (JSC)

?

?

This lecture is not considered to be a

full introduction to Python and Jupyter

and rather focusses on selected

commands and concepts relevant for

assignments in this course

The goal of this lecture is to make

course participants aware of the

Python environment they work with in

the light of the topics of this course

? Selected Python Demonstrations

?

?

?

?

?

Basic Variables & Hello World

Simple Loops & If Statements

Arrays & Vectors & Matrices

Data Preprocessing Application for Analysing Hand-Written Characters Data

Data Mining Application with Association Rule Mining using Simplified Retail Data

Practical Lecture 0.1 �C Short Introduction to Python & Jupyter

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Python Environments

Practical Lecture 0.1 �C Short Introduction to Python & Jupyter

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