2024-02-15 DLI Training Series - Fundamentals of Deep Learning (hdli4w23)

CourseDLI Training Series - Fundamentals of Deep Learning
Numberhdli4w23
Available places12
Date15.02.2024 – 15.02.2024
PriceEUR 0.00
LocationLeibniz Rechenzentrum
Boltzmannstr. 1
85748 Garching b. München
RoomKursraum 2
Registration deadline08.02.2024 23:59
E-maileducation@lrz.de


This is an on-site course at LRZ in Garching near Munich. There will be no possibility to join online remotely via video conference.

Participants are expected to bring their own laptops running the latest version of Chrome or Firefox. There are no PCs installed in the course room! 

Contents

Businesses worldwide are using artificial intelligence to solve their greatest challenges. Healthcare professionals use AI to enable more accurate, faster diagnoses in patients. Retail businesses use it to offer personalised customer shopping experiences. Automakers use it to make personal vehicles, shared mobility, and delivery services safer and more efficient. Deep learning is a powerful AI approach that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, and language translation. Using deep learning, computers can learn and recognise patterns from data that are considered too complex or subtle for expert-written software.

In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

The course is part of a training series co-organised by LRZ and NVIDIA Deep Learning Institute (DLI).  All instructors are NVIDIA certified University Ambassadors.

Learning Objectives

By participating in this workshop, you’ll:

  • Learn the fundamental techniques and tools required to train a deep learning model
  • Gain experience with common deep learning data types and model architectures
  • Enhance datasets through data augmentation to improve model accuracy
  • Leverage transfer learning between models to achieve efficient results with less data and computation
  • Build confidence to take on your own project with a modern deep learning framework

Important information

After you are accepted, please create an account under courses.nvidia.com/join.

Ensure your laptop / PC will run smoothly by going to http://websocketstest.com/ Make sure that WebSockets work for you by seeing under Environment, WebSockets is supported and Data Receive, Send and Echo Test all check Yes under WebSockets (Port 80).If there are issues with WebSockets, try updating your browser.

NVIDIA Deep Learning Institute

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help you get started with training, optimising, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.

Screen Shot 2017-12-13 at 12.24.46 

Prerequisites

An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and an understanding of how to compute a regression line.

Hands-On

The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done on a fully configured GPU-accelerated workstation in the cloud.

Language

English

Lecturers

PD Dr. Juan Durillo Barrionuevo (LRZ, NVIDIA certified University Ambassador)

Prices and Eligibility

The course is open and free of charge for people from academia from the Member States of the European Union (EU) and Associated Countries to the Horizon 2020 programme.

Registration

Please register with your official e-mail address to prove your affiliation.

Withdrawal Policy

See Withdrawal

Legal Notices

For registration for LRZ courses and workshops we use the service edoobox from Etzensperger Informatik AG (www.edoobox.com). Etzensperger Informatik AG acts as processor and we have concluded a Data Processing Agreement with them.

See Legal Notices


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Date

Time

Leader

Location

Room

Description

115.02.202410:00 – 17:00Juan Durillo Barrionuevo
LRZ Events
Leibniz RechenzentrumKursraum 2Lecture