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David Macedo proslijedio/la je Tweet
We’ve introduced the first large-scale data set and benchmark to help make conversation models more empathetic. Watch the video Research in Brief to learn more. https://youtu.be/lgTbWcBJq7k via
@YouTube Read the full paper: https://arxiv.org/pdf/1811.00207.pdf?fbclid=IwAR1Zvx7e3ry7mO3EaOQgo0KTzwRDgwJZGUnMO0Nx-YG9UZdxvHlm0uZl6D8 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
I wrote "How to solve 90% of NLP problems: a step-by-step guide" after seeing dozens of applied NLP projects at
@InsightFellows. It has been read by over three hundred thousand people! It presents a cookie cutter NLP approach, along with reference codehttps://mlpowered.com/posts/how-to-solve-90-nlp/ …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
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@BaiduResearch has already applied LinearFold to the 2019-nCoV, reducing prediction time from 55 minutes to 27 seconds.#CoronavirusOutbreak#nCoV2019#Health#Baidu#research#AI#Algorithmshttps://medium.com/syncedreview/baidu-open-sources-rna-prediction-algorithm-for-2019-novel-coronavirus-843dab75608f …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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David Macedo proslijedio/la je Tweet
Given that data loading can be a major bottleneck in many DL projects, this sounds like an interesting project to check out: "Accelerating Pytorch with Nvidia DALI" --> "on small models it's ~4X faster than the Pytorch dataloader"https://github.com/yaysummeriscoming/DALI_pytorch_demo …
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David Macedo proslijedio/la je Tweet
IIRC Fukushima's Neocognitron also used the max(0, x) function in its design (to mimic firing frequencies in biological neurons, which must be positive).
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David Macedo proslijedio/la je Tweet
Reminder: the neocognitron was published in 1979! https://twitter.com/rupspace/status/1224133745357099009 …pic.twitter.com/4wTQaXCX1P
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David Macedo proslijedio/la je Tweet
The 1986 classic 'Parallel Distributed Processing' uses the term 'threshold function' instead of 'rectified linear unit'. I prefer the 1986 version :)pic.twitter.com/qLB4GbKWsL
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David Macedo proslijedio/la je Tweet
This intro video about it from 1986 is just so retro and cool:https://www.youtube.com/watch?v=Qil4kmvm2Sw …
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David Macedo proslijedio/la je Tweet
This repo is full of amazing awesomeness. I don't know of anything else like it. Independent refactored carefully tested implementations of modern CNNshttps://twitter.com/wightmanr/status/1224178577593241602 …
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David Macedo proslijedio/la je Tweet
Added ImageNet validation results for 164 pretrained
#PyTorch models on several datasets, incl ImageNet-A, ImageNetV2, and Imagenet-Sketch. No surprise, models with exposure to more data do quite well. Without extra, EfficientNets are holding their own.https://github.com/rwightman/pytorch-image-models/tree/master/results …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
Our forthcoming book dives deep into different tabular modeling approaches, with many experiments. But I'll save you from reading the whole thing, and just show you the conclusion. https://www.amazon.com/Deep-Learning-Coders-fastai-PyTorch/dp/1492045527 …pic.twitter.com/XjuoDncjIn
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David Macedo proslijedio/la je Tweet
A welcome surprise when our
#fastdotai tabular models wind up beating baselines. GBT: 1.44, TabNet: 0.14, fastai: 0.034.Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
Wow, what a paper! Super Convergence is a super interesting phenomenon. Thanks
@jeremyphoward for the recommendation. [1708.07120] Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates https://arxiv.org/abs/1708.07120Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
We're standardizing OpenAI's deep learning framework on PyTorch to increase our research productivity at scale on GPUs (and have just released a PyTorch version of Spinning Up in Deep RL): https://openai.com/blog/openai-pytorch/ …pic.twitter.com/lgvqDdWDoB
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David Macedo proslijedio/la je Tweet
One of the best decisions we ever made
@nvidia Applied Deep Learning Research was to standardize on@PyTorch for all our research. It has made us more productive and made our work more fun. Glad to see@OpenAI agrees!https://openai.com/blog/openai-pytorch/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
Humans learn from curriculum since birth. We can learn complicated math problems because we have accumulated enough prior knowledge. This could be true for training a ML/RL model as well. Let see how curriculum can help an RL agent learn:https://lilianweng.github.io/lil-log/2020/01/29/curriculum-for-reinforcement-learning.html …
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David Macedo proslijedio/la je Tweet
Pandas 1.0 is here! * Read the release notes: https://pandas.pydata.org/pandas-docs/version/1.0/whatsnew/v1.0.0.html … * Read the blogpost reflecting on what 1.0 means to our project: https://dev.pandas.io/pandas-blog/pandas-10.html … * Install with conda / PyPI: https://pandas.pydata.org/pandas-docs/version/1.0.0/getting_started/install.html … Thanks to our 300+ contributors to this release.
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David Macedo proslijedio/la je Tweet
Transformers 2.4.0 is out
- Training transformers from scratch is now supported
- New models, including *FlauBERT*, Dutch BERT, *UmBERTo*
- Revamped documentation
- First multi-modal model, MMBT from @facebookai, text & images Bye bye Python 2
https://github.com/huggingface/transformers/releases …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
David Macedo proslijedio/la je Tweet
Today we announce a novel, open-source method for text generation tasks (e.g., summarization or sentence fusion), which uses edit operations instead of generating text from scratch, leading to less errors and faster model execution. Read about it below.https://goo.gle/38XfRXU
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