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+<!DOCTYPE html>
+<html>
+ <head>
+ <title>Title</title>
+ <meta charset="utf-8">
+ <style>
+ @import url(https://fonts.googleapis.com/css?family=Yanone+Kaffeesatz);
+ @import url(https://fonts.googleapis.com/css?family=Droid+Serif:400,700,400italic);
+ @import url(https://fonts.googleapis.com/css?family=Ubuntu+Mono:400,700,400italic);
+ @import url(https://fonts.googleapis.com/css?family=Abel:400,700,400italic);
+ @import url(https://fonts.googleapis.com/css?family=Ropa+Sans:400,700,400italic);
+ @import url(https://fonts.googleapis.com/css?family=Cabin:400,700,400italic);
+ @import url(https://fonts.googleapis.com/css?family=Roboto+Mono:400,700,400italic);
+
+ body { font-family: 'Arial'; font-size: 200%; color: #404040;}
+ h1, h2, h3 {
+ font-family: 'Cabin';
+ font-weight: 400;
+ color: #1F407A;
+ }
+
+
+
+ .remark-frontslide-content { padding: 0; border: 10 px solid blue; }
+ .remark-slide-content-large { font-size: 90%; }
+ .remark-slide { border: 10 px solid blue; }
+ .remark-slide-content h1 { font-size: 3em; }
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+ .remark-slide-content h3 { font-size: 1.6em; }
+ .remark-slide-content-large h1 { font-size: 2em; }
+ .remark-slide-content-large h2 { font-size: 1.6em; }
+ .footnote {
+ position: absolute;
+ bottom: 3em;
+ }
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+ display: block;
+ -webkit-margin-before: 0em;
+ -webkit-margin-after: 0em;
+ -webkit-margin-start: 0px;
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+ -
+ li p { line-height: 1.25em; }
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+ .large { font-size: 2em; }
+ a, a > code {
+ color: #404040;
+ text-decoration: none;
+ font-family: 'Ubuntu Mono';
+ }
+
+ .inverse {
+ background: #1F407A;
+ color: #777872;
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+ .remark-code-line-highlighted { background-color: #373832; }
+ .pull-left {
+ float: left;
+ width: 47%;
+ }
+ .pull-right {
+ float: right;
+ width: 47%;
+ }
+ .pull-right ~ p {
+ clear: both;
+ }
+ #slideshow .slide .content code {
+ font-size: 0.8em;
+ }
+ #slideshow .slide .content pre code {
+ font-size: 0.9em;
+ padding: 15px;
+ }
+ strong {
+ color: #E67116;
+ }
+
+
+
+ .remark-code, .remark-inline-code { font-family: 'Cabin';}
+ </style>
+ </head>
+ <body>
+ <textarea id="source">
+
+class: inverse, center, middle, remark-frontslide-content
+<img src="./front_page.png" width=100%/>
+
+---
+class: center, middle, inverse, remark-slide-content-large
+
+# About us
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+
+- IT Services close to research
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+
+- IT Services close to research
+
+
+- Zoo of experts with diverse background
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+
+- IT Services close to research
+
+
+- Zoo of experts with diverse background
+
+
+### Here today:
+
+* Dr. Tarun Chadha
+
+
+* Dr. Mikolaj Rybinski
+
+
+* Dr. Uwe Schmitt
+
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+
+
+- Scientific Visualization
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+
+
+- Scientific Visualization
+
+
+
+- Consulting and Training: Code Clinics, ...
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+
+
+- Scientific Visualization
+
+
+
+- Consulting and Training: Code Clinics, ...
+
+
+- Research Data Management
+
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+
+
+- Scientific Visualization
+
+
+
+- Consulting and Training: Code Clinics, ...
+
+
+
+- Research Data Management
+
+
+
+- Research Data Analysis
+
+
+---
+class: remark-slide-content-large
+
+
+## About Scientific IT Services (SIS)
+- Scientific Computing Services: Euler, ...
+
+
+
+- Data Science Support
+
+
+- Software Development: openBIS, ...
+
+
+
+- Scientific Visualization
+
+
+
+- Consulting and Training: Code Clinics, ...
+
+
+- Research Data Management
+
+
+
+- Research Data Analysis
+
+
+- Personalized Health Data Services
+
+---
+class: center, middle, remark-slide-content-large
+
+<span style="font-size: 200%; color: #1F407A;">
+Contact us !
+<br/>
+<br/>
+https://sis.id.ethz.ch/
+</span>
+
+---
+class: center, middle, inverse, remark-slide-content-large
+
+# About the course
+
+---
+class: remark-slide-content-large
+
+# About the course
+
+
+* First version, might be a bit rough, not sure if time planning is good.
+
+---
+class: remark-slide-content-large
+
+# About the course
+
+
+* First version, might be a bit rough, not sure if time planning is good.
+
+
+* Pragmatic approach, little math.
+
+---
+class: remark-slide-content-large
+
+# About the course
+
+
+* First version, might be a bit rough, not sure if time planning is good.
+
+
+* Pragmatic approach, little math.
+
+
+* Introduction only !
+
+---
+class: remark-slide-content-large
+
+# About the course (2)
+
+What will you learn ?
+
+* Basic concepts of Machine Learning (ML).
+
+---
+class: remark-slide-content-large
+
+# About the course (2)
+
+What will you learn ?
+
+* Basic concepts of Machine Learning (ML).
+
+
+* More classical machine learning than artificial neural networks.
+
+---
+class: remark-slide-content-large
+
+# About the course (2)
+
+What will you learn ?
+
+* Basic concepts of Machine Learning (ML).
+
+
+* More classical machine learning than artificial neural networks.
+
+
+* General overview of supervised learning and related methods.
+
+
+---
+class: remark-slide-content-large
+
+# About the course (2)
+
+What will you learn ?
+
+* Basic concepts of Machine Learning (ML).
+
+
+* More classical machine learning than artificial neural networks.
+
+
+* General overview of supervised learning and related methods.
+
+
+* How to start with ML using `scikit-learn` and `Keras`.
+
+
+---
+class: remark-slide-content-large
+
+# About the course (3)
+
+
+What will you NOT learn?
+
+
+* How to program with Python.
+
+
+---
+class: remark-slide-content-large
+
+# About the course (3)
+
+
+What will you NOT learn?
+
+
+* How to program with Python.
+
+
+* How exactly ML methods work.
+
+
+---
+class: remark-slide-content-large
+
+# About the course (3)
+
+
+What will you NOT learn?
+
+
+* How to program with Python.
+
+
+* How exactly ML methods work.
+
+
+* Unsupervised learning methods.
+
+---
+class: center, middle, inverse, remark-slide-content-large
+
+# Schedule
+
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+- Chapter 1: General Introduction to Machine Learning
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+- Chapter 1: General Introduction to Machine Learning
+
+
+
+- Chapter 2: Introduction to Classification
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+- Chapter 1: General Introduction to Machine Learning
+
+
+
+- Chapter 2: Introduction to Classification
+
+
+
+- Chapter 3: Overfitting and Cross Validation
+
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+- Chapter 1: General Introduction to Machine Learning
+
+
+
+- Chapter 2: Introduction to Classification
+
+
+
+- Chapter 3: Overfitting and Cross Validation
+
+
+- Chapter 4: Measuring Quality of a Classifier
+
+---
+class: remark-slide-content-large
+
+# Day 1
+
+- Chapter 0: Quick Introduction to numpy, pandas, matplotlib
+
+
+- Chapter 1: General Introduction to Machine Learning
+
+
+
+- Chapter 2: Introduction to Classification
+
+
+
+- Chapter 3: Overfitting and Cross Validation
+
+
+- Chapter 4: Measuring Quality of a Classifier
+
+
+- Chapter 5: Classification Algorithms Overview
+
+
+---
+class: remark-slide-content-large
+
+# Day 2
+
+- Chapter 6: Pipelines and Hyperparameter Optimisation
+
+---
+class: remark-slide-content-large
+
+# Day 2
+
+- Chapter 6: Pipelines and Hyperparameter Optimisation
+
+
+- Chapter 7: Introduction to Regression
+
+---
+class: remark-slide-content-large
+
+# Day 2
+
+- Chapter 6: Pipelines and Hyperparameter Optimisation
+
+
+- Chapter 7: Introduction to Regression
+
+
+- Chapter 8: Introduction to Neural Networks
+
+---
+class: center, middle, inverse, remark-slide-content-large
+
+# Quick poll
+
+---
+class: remark-slide-content-large
+
+# Who used ... before ?
+
+- Jupyter Notebooks
+
+
+---
+class: remark-slide-content-large
+
+# Who used ... before ?
+
+- Jupyter Notebooks
+
+
+- Pandas
+
+---
+class: remark-slide-content-large
+
+# Who used ... before ?
+
+- Jupyter Notebooks
+
+
+- Pandas
+
+
+- Matplotlib
+
+---
+class: remark-slide-content-large
+
+# Who used ... before ?
+
+- Jupyter Notebooks
+
+
+- Pandas
+
+
+- Matplotlib
+
+
+- seaborn
+
+---
+class: remark-slide-content-large
+
+# Who used ... before ?
+
+
+- Jupyter Notebooks
+
+
+- Pandas
+
+
+- Matplotlib
+
+
+- seaborn
+
+
+- numpy
+
+
+---
+class: center, middle, inverse, remark-slide-content-large
+
+# Questions ?
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+1. Start Computer, chose `fedora` during startup
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+1. Start Computer, chose `fedora` during startup
+
+
+2. Login with your `NETHZ` credentials
+
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+<p>1. Start Computer, chose `fedora` during startup
+<br/>
+<br/>
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+<p>1. Start Computer, chose `fedora` during startup
+<br/>
+<br/>
+<p>2. Login with your `NETHZ` credentials
+<br/>
+<br/>
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+<p>1. Start Computer, chose `fedora` during startup
+<br/>
+<br/>
+<p>2. Login with your `NETHZ` credentials
+<br/>
+<br/>
+
+
+<p>3. Start Terminal (click `activity` top-left corner)
+<br/>
+<br/>
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+<p>1. Start Computer, chose `fedora` during startup
+<br/>
+<br/>
+<p>2. Login with your `NETHZ` credentials
+<br/>
+<br/>
+
+
+<p>3. Start Terminal (click `activity` top-left corner)
+<br/>
+<br/>
+
+
+<p>4. Enter <br/><br/><div style="font-family: Ubuntu Mono; font-size: .8em;"><center>curl https://sis.id.ethz.ch/mlw/install.sh | bash</center></div>
+<br/>
+<br/>
+
+---
+class: remark-slide-content-large
+
+# Get started
+
+<p>1. Start Computer, chose `fedora` during startup
+<br/>
+<br/>
+<p>2. Login with your `NETHZ` credentials
+<br/>
+<br/>
+
+
+<p>3. Start Terminal (click `activity` top-left corner)
+<br/>
+<br/>
+
+
+<p>4. Enter <br/><br/><div style="font-family: Ubuntu Mono; font-size: .8em;"><center>curl https://sis.id.ethz.ch/mlw/install.sh | bash</center></div>
+<br/>
+<br/>
+
+
+
+<p>5. Wait and press `ENTER` when asked
+
+
+
+ </textarea>
+ <script src="https://remarkjs.com/downloads/remark-latest.min.js">
+ </script>
+ <script>
+ var slideshow = remark.create();
+ </script>
+ </body>
+</html>