Namaste! Last week I spent two excellent days at Mercedes Benz Consulting. Down in the German South. Leinfelden-Echterdingen close to Stuttgart. It was great coming back. You know, my job is to travel and teach the “trinity” Artificial Intelligence, Machine Learning and Deep Learning. Deep Learning being my specialty. This time I trained around a dozen people. Highly motivated experts from many different departments and subsidiaries of Daimler AG. What a pleasure! Today I feel a little exhausted. But very, very accomplished! Because I strongly believe that I pushed to topic forward. At least a little!
Remember the old days?
The old days, when Mercedes Benz was a prime example of disruption? I am not saying that those days are long gone… No. What I wanted to say is that the Benz Patent-Motorwagen was part of something gigantic. If you doubt that ask yourself: How many horses do you see on the streets nowadays?
Today, we are facing the zenith of another disruptive technology: Artificial Intelligence. You can literally watch the tech getting more and more accessible. On an everyday basis you see new and successful use-cases. I do. You remember all my mantras… One is: Today everyone can do Artificial Intelligence. And when it comes to the special field Deep Learning, all you need to do is learn and apply. But how?
Teaching means getting people to use their brain and hands.
In my world it is essential that you learn technology hands-on. Do you want to become a Deep Learning expert? Please do yourself a favour and strife towards a learning-by-doing attitude. Of course you can read a lot about Deep Learning. But if you really want to get something on the metaphorical and even literal road: Do it. The practical approach to learning saves you a lot of time. Trust me. I always see this.
“Do it” is my main-message in all my trainings. If there is a question about a very special detail, why not doing an experiment instead of digging deeply into the literature? Deep Learning for me seems to become more “1% theory and 99% practice” like Yoga.
Whoa, I did a lot of trainings this year. All over the nation. At schools, universities, small companies, start-ups and now at a big company Daimler AG. It is not a secret that I spent quite some time in the automotive sector in the past. I worked for Volkswagen and Porsche, I maintained contacts to Audi AG and BMW. One of the reasons why I felt immediately at home at Leinfelden-Echterdingen.
The path towards Deep Learning is a short one.
For me it is important the get this idea across: You can do Deep Learning on your own hardware. No need for special hardware. At least in the beginning. Later when your prototypes and their data grow, get some GPU-power. In the past, I saw Deep Learning on Lenovo Thinkpads, Macs, Surfaces and even once on an iPhone. That is why I usually ask the participants of my trainings to prepare their machines in advance and get them development-ready. This always works like a charm. People do all the magic where they feel most comfortable. And they take many things home with them.
At Daimler AG we dedicated a lot fruitful time to clearing the rumour-house. You know, the topic at hand nowadays appears on too many Powerpoint slides without the proper understanding. “Deep Learning is a part of Machine Learning is a part of Artificial Intelligence”. This poem is very easy and could prevent you from saying that Machine Learning and Artificial Intelligence are two different fields. On top of that, you can do many things with Deep Learning in special and Machine Learning in general. You cannot solve all the problems. But many. There is a lots of use-cases readily available and waiting to be adapted to the needs and data of Daimler AG. There is a great future awaiting.
My two days at Daimler AG were filled with lots and lots of very productive discussions and many exercises in Deep Learning. Jupyter notebooks, Keras, Tensorflow, Natural Language Processing, classifications, regressions, Deep Learning for image- and sound-processing, just to name a few things we explored. I am very happy for that. Today, I am a little sad that those two days went by so quickly.
The end may be a beginning.
For me it is always great if many questions are answered and a couple of them are open. Truth be told, you cannot conquer Deep Learning in two days. The two-day course was a mere introduction to a huge field. We just touched on advanced topics like Representation Learning and Reinforcement Learning with Neural Networks. Maybe I will be back next year.
I feel very honoured that I had this excellent opportunity to teach at Daimler AG. I am humbled by the fact that I got selected as a teacher. And I hope that I moved the company a little forward when it comes to Deep Learning. The company is on a very good path. Thanks a lot for the organisers in the South. I owe you. Namaste.
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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 email@example.com - I am looking forward to talking to you!