Last ever release of tensorflow 1.x .
https://app.releasly.co/releases/tensorflow/tensorflow/1_15_0
Including various API’s from V2, better GPU support, and lots of bug fixes!
submitted by /u/combarnea
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Eg:
“An embarrassingly simple approach to zero-shot learning”, Bernardino Romera-Paredes and Philip H. S. Torr.
“Attention Is All You Need”, Ashish Vaswani et al.
“Cats and dogs”, Omkar M Parkhi et al.
submitted by /u/EveryDay-NormalGuy
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https://sites.google.com/view/berkeley-cs294-158-sp19/home
Pieter Abbeel’s UC Berkeley class (videos and materials) from Spring 2019 on Deep Unsupervised Learning covering a span of topics: Autoregressive Models, Flow Models, VAEs, GANs, Self-Supervised Learning, Representation Learning for RL, and guest lectures from Ilya Sutskever, Alyosha Efros, Alec Radford and Aaron van den Oord.
submitted by /u/PuzzledForm
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I am looking for a way to monitor the balance between the training of the discriminator (D) and the generator (G) in GANs. I am aware of numerous heuristic as well as non-heuristic ways to stabilize the training (minibatch discrimination, label smoothing, crippling the discriminator, GP and many others), but I haven’t found a method that would ideally provide a scalar value denoting the balance between training.
The obvious questions is to compare losses of D and G, or their gradients. However, this is extremely noisy and I believe that there should be a better/different way to measure it out there. A different take on it is to consider for example FID as the scalar value denoting the balance. If you know of any methods, let me know!
submitted by /u/mw_molino
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Out of the most random curiosity:
Who is expanding their knowledge and application for ML/DL/AI in investment management; specifically, to create alpha from unstructured and/or alternative data?
The fin tech industry is the FUTURE of Finance and Technological conglomerates of society. The future is now.
L has to be greater than or equal to C; where L represent the learning spectrum and C represent change.
I need some insight on where to find a how-to start up quite to help me in my endeavors of creating ML/DL algorithms and AI systems. I have some experience in Python*
Thoughts? Recommendations?
submitted by /u/ddias19
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https://github.com/sepandhaghighi/pycm
submitted by /u/sepandhaghighi
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![[P] Headliner, a new sequence modeling library that eases the training and in particular, the deployment of custom sequence models](https://b.thumbs.redditmedia.com/fSS4PP9Dy7IN6E2SlQ4jwzbSz6EeBkmEKYT5RfH7igE.jpg "[P] Headliner, a new sequence modeling library that eases the training and in particular, the deployment of custom sequence models") |
We’ve just open-sourced our library headliner which is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models. It was originally built for our own research at Axel Springer AI to generate headlines from Welt news articles (see figure 1). That’s why we chose the name, Headliner. Although this library was created internally to generate headlines, you can also use it for other tasks like machine translations, text summarization and many more. Figure 1: One example from our Welt.de headline generator. We built this library with the following goals in mind: 🚀 Simple API for training and deployment (only a few lines of code) ➡️ Uses TensorFlow 2.0 with all its new features ⚙️ Modular classes: text preprocessing, modeling, evaluation and easily extensible for different encoder-decoder models 📄 Works on large text data Headliner is our first NLP project that we open-sourced and we’re happy about this. Please try out our library, ⭐️ it on Github and spread the word! We’d love to get feedback. #deeplearning #machinelearning #NLP 🔤 Github: https://github.com/as-ideas/headliner submitted by /u/datitran |
I’m starting to get into ML and I’m curious what monitor setup you guys are using. My GPU supports up to 4 monitors but at the moment I just use an old single one (1440×900). I could also get one really wide one (one of those curved gamer ones) if you thought it was reasonable.
What is your setup? What do you recommend for a (reasonable) budget?
submitted by /u/Regressionmodel4
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BPE (Byte Pair Encoding) seems to be a natural choice of word representation for morphologically rich languages. However, I wonder what your experiences with using different representations (such as n-grams, word2vecs, etc.) are?
submitted by /u/ai_think
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