Upcoming Workshops

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Recent Events

Generative Adversarial Networks
When: 2017-11-28
Where: HP Auditorium
35 people came
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Do you want to learn about one of the most important advances to deep learning in the past 10 years? Do you want to make neural networks that generate realistic images that don't exist in nature?

Come to Machine Learning at Berkeley's last workshop of the semester on Generative Adversarial Networks to learn about how you can use this unsupervised learning algorithm to do all of this and more.

You can find the installation instructions here: (1) Python: (2) Tensorflow: (3) Keras:

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Machine Learning at Berkeley added 2 new photos.
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A huge congratulations to ML@B’s Riley Edmunds, Noah Golmant, Vinay Ramasesh, Phillip Kuznetsov, Piyush Patil, and Raul Puri for presenting their work and winning a research prize at the Deep Learning Security Workshop 2017 (DLSW ’17) in Singapore! This ML@B research team has been studying the susceptibility of meta-learning models to adversarial attacks, in order to build secure machine learning models. Thank you professor Dawn Song for co-chairing the event!

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Machine Learning at Berkeley shared UC Berkeley Division of Data Science's video.
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Thank you UC Berkeley Division of Data Science for the spotlight on our research project SLANG!

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Phillip Kuznetsov shared a post to your timeline.

Checkout this thing I've been working on for over a year with a team of amazing people (and a dope lead Jordan Prosky). Come take our classes if you're enrolled at UC Berkeley! If you're not or don't think you have time, we'll be uploading all of our materials online as well.

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Machine Learning at Berkeley is with Renee Sweeney and 3 others.
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As the semester comes to an end, ML@B is opening up research proposals for next semester. If you have an idea for a research project in machine learning or artificial intelligence, and want to take advantage of ML@B’s resources (including compute resources, a research team, and grants), please submit a proposal below by May 12th.

Independent Research Application:

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Machine Learning at Berkeley is feeling thankful with Ted Xiao and 4 others.
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We are thrilled to have Ian Goodfellow come and talk about his work in generative models and GANs!

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Machine Learning at Berkeley is with Okoshi and 2 others.
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Machine Learning at Berkeley is thrilled to partner with The House! We look forward to all the exciting collaborations to come!

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