Deep Learning Tour through Germany

Namaste! I just came back from a two weeks tour through Germany. What happened? Deep Learning Training galore! In the very first week, I visited Data Science Retreat in Berlin. In the second week, I went to Paessler AG in Nuremberg. I still feel a little tired. But very, very accomplished.

You know, one of the bigger parts of my business is teaching Deep Learning. I have the strong conviction that Germany and Europe are on their way. I am optimistic that they are to become major contributors to Artificial Intelligence in industry. Well, USA and China are on the lead. No doubt about that. But we Europeans still have a great chance to reduce the distance. How? Learn and apply! There are many low hanging fruits out there!

Quality time at Data Science Retreat.

I spent a gorgeous week at Data Science Retreat. For the fourth time this year. I am their Deep Learning trainer. And it is always an honor to me to open the curriculum with my Deep Dive into Deep Learning. Again, I had the lovely chance to teach for five days. Starting with a handful of Python basics and then headfirst into Deep Learning. A little theory first and then practice!

A well known Yoga teacher once said something significant. The late Sri K. Pattabhi Jois spoke: Yoga is 99 percent practice and 1 percent theory. I believe something like that is also true for Deep Learning.

Of course you can fill many and many more Powerpoint slides with buzzwords. Everything you learned from a Udemy course about Artificial Intelligence, Machine Learning and Deep Learning over the weekend. All on a huge slide-deck. But all those slides are not going to help if you do not put them into action. You have to build a solid foundation of practical knowledge.

And this is what I make extra sure every time I teach. Of course, I talk a lot and the students take their notes. But all my work would be useless if the students would not train one Artificial Neural Network after the other. Nothing would last if the students would not apply Deep Learning to one domain after the other. Muscle memory. You see what I mean?

Coming back to Data Science Retreat. Oh, how warmhearted this group was! It was really sad leaving them after an intense week. But I will be back!

At Paessler AG in Nuremberg.

In the second week I went to Paessler AG in Nuremberg, Bavaria. And I am very happy. And there is a reason for that. You see, for me it is obvious that Deep Learning has many use-cases everywhere. And I am very thankful for each and every company that decides to learn about the topic at hand.

Remember Sir Arthur Charles Clarke? British science-fiction writer. The guy who was responsible for Stanley Kubrick’s excellent movie 2001. Here are three excellent quotes from him:

  1. When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.
  2. The only way of discovering the limits of the possible is to venture a little way past them into the impossible.
  3. Any sufficiently advanced technology is indistinguishable from magic.

Paessler AG showed a lots of motivation and courage. Decision makers obviously realized that it is about time to learn about Deep Learning. For many people Deep Learning is indistinguishable from magic (see above). And I love to either teach magic or demystify it. Depending on perspective.

I started with half a day of high level interactive lecture/discussion/workshop. Around 35 curious individuals attended. I made sure that all of them got an adequate understanding about what is going on. After that I taught Deep Learning for three days in a row. What a joyride! The room was filled with more than a dozen highly motivated software engineers. They really challenged me with their curiosity and their thousands of questions. I guess this was for me the fastest Deep Learning training ever. High speed! The participants really made sure that they learn a lot from me. I am most thankful!

A tiny detail… Here is the cat. I usually explain Convolutional Neural Networks and their visual hierarchies with an example. Here it is:

The idea is that CNNs decompose images into a so called visual hierarchy. A cat consists of body parts. Each body part consists of details. Each detail is a combination of colored areas. And those are combinations of edges. Just a little theory.

The future is already there in Nuremberg.

Almost a side note. There was a moment of positive shock for me in Nuremberg. After using the local subway for around three days on a daily basis, I found myself standing in the front. Standing in the front watching us moving through the tunnel. And then I realized… Something is different! I could watch the tunnel, because that goddamn (sorry… language) train did not have a human driver! What a moment!

Here is a nice photo if the self-driving train:

More future for us.

Call me an optimist. I am happy to call myself one. The Deep Learning chapter did just begin for Europe and Germany. I see more and more companies embracing Deep Learning as a technology with the capacity to contribute a lot. They got all the data, all the use-cases. And they got a lot of skills already sleeping in-house. That is why I am very delighted every time I wake up some talents to Deep Learning. And I don’t care if it is Nuremberg, Berlin or beyond!

Stay in touch.

I hope you liked the article. Why not stay in touch? You will find me at LinkedIn, XING and Facebook. Please add me if you like and feel free to like, comment and share my humble contributions to the world of AI. Thank you!

If you want to become a part of my mission of spreading Artificial Intelligence globally, feel free to become one of my Patrons. Become a Patron!

A quick about me. I am a computer scientist with a love for art, music and yoga. I am a Artificial Intelligence expert with a focus on Deep Learning. As a freelancer I offer training, mentoring and prototyping. If you are interested in working with me, let me know. My email-address is - I am looking forward to talking to you!

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