Slides and sample files are available at https://drive.google.com/drive/folders/1IRz_2izq38y9g_P1eTYZPEsqbywXDu6D?usp=sharing

Debunk the myth that Machine Learning is difficult. Tensorflow is Google’s open-source framework for mathematical, machine learning and deep learning capabilities that makes building machine learning models easier. Deep learning algorithms are a machine learning research area that studies on automated learning of features at multiple levels of abstraction. Walk through the basics with us to explore the broader scope of AI.

This will be a hybrid event! While we have a speaker at a venue open to attendees, if you would prefer to attend virtually, you can join the live stream session instead. This will be our first event using this format, so please be gracious with any hiccups or opportunities for improvement.

Note: The venue has a requirement that all attendees be fully vaccinated against COVID-19. The health of our attendees and the venue staff is our highest priority and we appreciate your understanding.

Agenda:

1. Welcome
2. Intro to ML and What's deep learning
3. Concepts of Neural Networks
4. Getting started with TensorFlow for Neural Networks
5. Shallow vs. Deep Neural networks (hands-on TensorFlow)

Since this is a heavier and longer topic, we probably won't have time for much networking at the end of the event. Watch out for future event announcements for more networking and learning opportunities.

Location:

T-Mobile Accelerator

One Kansas City Place

1200 Main St, Ste 2450

Kansas City, MO 64105

Parking:

The venue has suggested not parking in the attached garage as it closes at 7 and sometimes causes issues getting out. You can see other available public garages and lots on the downtown Kansas City website (https://www.visitkc.com/visitors/getting-around/maps/downtown-parking-map). 

We won't be able to validate any parking. However, there is a street car stop directly in front of the venue, so there are plenty of options. As a reminder, RideKC has many free options now which can be easily found using their app (https://ridekc.org/fares/transit-app).