Recap of the 2019 Predictive Analytics World and Deep Learning World Conferences

I spoke at and attended the co-located Predictive Analytics World and Deep Learning World conferences. The bottom line: the event was really good — I give it an overall grade of an A- which is (tied for) the best grade I’ve ever given to any conference. See

The conference ran from June 15-20, 2019 and was at Caesars Palace in Las Vegas. I estimate there were about 2,000 attendees, speakers, staff, and exhibitors there, but I could be way off with my count because the event was spread out a bit. Attendees came from all types of companies and had a wide range of job titles and backgrounds. I talked to people from financial and insurance companies, hospitals and medical companies, tech companies, and state and federal government agencies.

The workshop I taught had about 80 attendees.

I did an all-day hands-on neural networks workshop. It went very well. We covered a huge amount of information. Attendees installed the TensorFlow and Keras code libraries (learning about Python package hell and how to deal with it) and then used Keras to explore deep classification and regression. We also looked at sentiment analysis using an LSTM, image classification using a CNN, and reinforcement learning multi-armed bandit algorithms and a Q-learning problem.

The Predictive Analytics World (PAW) event has been around for several years. PAW had several tracks covering topics such as business, financial, health care, and so on. I sat in on a few of the talks and they were all interesting.

This was the second year for the Deep Learning World (DLW) event. DLW is exceptionally good for a relatively new event. The topics were interesting and contained no fluff, and the speakers were good.

There were a lot of interesting companies at the conference Expo.

The Expo was excellent too. There were all kinds of interesting companies represented. For example, DataRobot ( ) was a primary sponsor and I was impressed with what their representatives had to say. I also liked Wolfram ( ), Metis ( ), and Deep Data Analytics ( ) . At most conference Expos, I’m only interested in a couple of exhibitors, but at PAW/DLW almost every single exhibitor caught my attention.

Usually, when I’m speaking at a conference, by the end of the third day, I’m more than ready to go home. But at PAW/DLW I really wanted to stay an extra day to listen to the talks, visit more of the companies at the event Expo, and chat with other attendees. I learned a lot and gained valuable insights about how companies are applying machine learning and AI. This information is directly applicable to my work.

In short, I give Predictive Analytics World and Deep Learning World a strong thumbs-up. If you work with machine learning, predictive analytics, data science, or have an interest in these topics, check out the conferences and if they’re aligned with your background and goals, give strong consideration to attending in 2020 — I know I’ll be there if I can.

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