Slides from my JAX 2018 talk: Deep Learning – a Primer

[This article was first published on Shirin's playgRound, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Here I am sharing the slides for a talk that my colleague Uwe Friedrichsen and I gave about Deep Learning – a Primer at the JAX conference on Tuesday, April 24th 2018 in Mainz, Germany.

Slides can be found here: https://www.slideshare.net/ShirinGlander/deep-learning-a-primer-95197733

Deep Learning is one of the “hot” topics in the AI area – a lot of hype, a lot of inflated expectation, but also quite some impressive success stories. As some AI experts already predict that Deep Learning will become “Software 2.0”, it might be a good time to have a closer look at the topic. In this session I will try to give a comprehensive overview of Deep Learning. We will start with a bit of history and some theoretical foundations that we will use to create a little Deep Learning taxonomy. Then we will have a look at current and upcoming application areas: Where can we apply Deep Learning successfully and what does it differentiate from other approaches? Afterwards we will examine the ecosystem: Which tools and libraries are available? What are their strengths and weaknesses? And to complete the session, we will look into some practical code examples and the typical pitfalls of Deep Learning. After this session you will have a much better idea of the why, what and how of Deep Learning, including if and how you might want to apply it to your own work. https://jax.de/big-data-machine-learning/deep-learning-a-primer/

To leave a comment for the author, please follow the link and comment on their blog: Shirin's playgRound.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)