Introduction to Deep Learning

Netherlands eScience Center

Online

January 25 - 27, 2022

9:00 - 13:00 CET

Instructors: Sven van der Burg, Djura Smits

Helpers: Cunliang Geng, Robin Richardson, Giordano Lipari

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General Information

The Digital Skills programme at the Netherlands eScience Center focuses on the foundational digital skills needed to put reproducible research into practice. The workshops we run cover the essentials of version control, online collaboration, reproducible code and good programming practices.

This is an hands-on introduction to the first steps in Deep Learning, intended for researchers who are familiar with (non-deep) Machine Learning.

The use of Deep Learning has seen a sharp increase of popularity and applicability over the last decade. While Deep Learning can be a useful tool for researchers from a wide range of domains, taking the first steps in the world of Deep Learning can be somewhat intimidating. This introduction aims to cover the basics of Deep Learning in a practical and hands-on manner, so that upon completion, you will be able to train your first neural network and understand what next steps to take to improve the model.

We start with explaining the basic concepts of neural networks, and then go through the different steps of a Deep Learning workflow. Learners will learn how to prepare data for deep learning, how to implement a basic Deep Learning model in Python with Keras, how to monitor and troubleshoot the training process and how to implement different layer types such as convolutional layers.

Who: 

Learners are expected to have the following knowledge:

  • Basic Python programming skills and familiarity with the Pandas package.
  • Basic knowledge on Machine learning, including the following concepts: Data cleaning, train & test split, type of problems (regression, classification), overfitting & underfitting, metrics (accuracy, recall, etc.).

Where: This training will take place online. The instructors will provide you with the information you will need to connect to this meeting.

When: January 25 - 27, 2022.

Requirements: Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Accessibility: We are dedicated to providing a positive and accessible learning environment for all. Please notify the instructors in advance of the workshop if you require any accommodations or if there is anything we can do to make this workshop more accessible to you.

Contact: Please email or training@esciencecenter.nl for more information.


Code of Conduct

Participants are expected to follow those guidelines:

Syllabus

Introduction

Classification by a Neural Network using Keras

Monitor the training process

Networks are like onions

Schedule

Day 1

Day 2

Day 3


Setup

To participate in this workshop, you will need access to software as described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

Install the videoconferencing client

If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.

Set up your workspace

Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:

This blog post includes detailed information on how to set up your screen to follow along during the workshop.

Please follow these setup instructions in preparation for the workshop.