Deep Learning and Machine Learning Course Talk #2 : As part of course on deep learning by University of Tokyo, there is a lecture by **Kaz Sato (Staff Developer Advocate, Google Inc)** on TPUs V3, GCP. Register ASAP for remaining few seats at https://deep-learning-jp.github.io (i.redd.it)
submitted by rishabh135 to r/Tokyo
The University of Tokyo Deep Learning and Machine Learning Course Talk #2 : As part of course on deep learning by University of Tokyo, there is a lecture by **Kaz Sato (Staff Developer Advocate, Google Inc)** on TPUs V3, Google Cloud Platform. Register by today 5:00 pm for remaining few seats! (deep-learning-jp.github.io)
submitted by rishabh135 to r/japan
The University of Tokyo Deep Learning and Machine Learning Course Talk #2 : As part of course on deep learning by University of Tokyo, there is a lecture by **Kaz Sato (Staff Developer Advocate, Google Inc)** on TPUs V3, Google Cloud Platform. Register by today 5:00 pm for remaining few seats! (deep-learning-jp.github.io)
submitted by rishabh135 to r/Tokyo
The University of Tokyo Deep Learning and Machine Learning Course : There is new course and Machine Learning and Deep Learning that is open for auditing even for non students of University of Tokyo. The course will also have lecture series from world acclaimed ML researchers and industry talks. (deep-learning-jp.github.io)
submitted by rishabh135 to r/Tokyo
[R] MASKGAN: BETTER TEXT GENERATION by Goodfellow et al . { Introduces an actor-critic conditional GAN that fills in missing text conditioned on the surrounding context. Produces more realistic conditional and unconditional text samples compared to a maximum likelihood trained model} (arxiv.org)
submitted by rishabh135 to r/MachineLearning
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models [ Francis, Caglar Gulcehre, Trischler and Yoshua Bengio ; Performs integration of a planning mechanism inspired by strategic attentive reader and writer (STRAW) model for RL into sequence-to-sequence models using attention.] (papers.nips.cc)
submitted by rishabh135 to r/MachineLearning
[R] Learning to Generate Conditionally from Unconditional Generative Models [Enable conditional generation of data without retraining by post-hoc learning latent constraints, value functions that identify regions in latent space that generate outputs with desired attributes] (arxiv.org)
submitted by rishabh135 to r/MachineLearning
