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Tuesday, March 10 2020
6:00pm - 9:00pm

ML/DL Project Cluster @Capital One ( AI Machine & Deep Learning )

This is a weekly PROJECT CLUSTER where attendees have time to work on projects that involve AI Machine or Deep Learning in a helpful and supportive environment. Many people who attend are using a fastai library on top of PyTorch to build models. Others use Keras and TensorFlow or Swift4TensorFlow. All are welcome! This group is for intermediate level coders and ML/DLnewcomers through experienced practitioners. (Bring your laptop & charger.) This Project Cluster is sponsored by Capital One. We submit a list of names to their security at 3pm the Monday prior to the meetup. If you have not RSVPed by then, we cannot guarantee you entrance, but normally the security guard will take your name and let you in if you show up. __Project Cluster Agenda__:** 6:00 - 6:45 (45m) Get online, meet your seat neighbors, & start work** 6:45 - 7:00 (15m) Welcome & project updates** 7:00 - 9:00 (2h) Get more work done! We strongly recommend that ML/DL newbies watching a fast.ai course video (course.fast.ai/) or one of Andrew Ng’s videos before asking others for help. You can watch videos (with headphones) at the study group. Join our Slack Workspace (bit.ly/JoinSlackFastSFbay) and channel #sg-sf (stands for "study group - sf") to share links or for questions about logistics flag @Deena & @Molly. We prefer you post code on the forum (forums.fast.ai/). Get to know your hosts:Deena: www.linkedin.com/in/deena-blumenkrantz/Molly: www.linkedin.com/in/molly-beavers-651025118/Sandeep: www.linkedin.com/in/sandeep-narayanaswami-60b16a64/ All attendees are expected to abide by the Code of Conduct:bit.ly/LadyNerds-CoC If you avoid social media and therefore cannot sign up via meetup, you are still welcome to these events, please DM @Molly and @Deena via Slack. For more information check out these links:fast.ai home page: www.fast.ai/fastai forum: forums.fast.ai/PyTorch: pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.htmlKeras: keras.io/TensorFlow: www.tensorflow.org/tutorials/images/deep_cnnChainer: github.com/chainer/chainer


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