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Good hyperparameters lead to ML success!
Learn how you can find the best parameters with Keras Tuner— a fully-featured, scalable, and easy-to-use hyperparameter tuning library for Keras and beyond.
Read the blog → https://goo.gle/2uCnJzt pic.twitter.com/LbsX9ux856
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New paper: Towards a Human-like Open-Domain Chatbot. Key takeaways: 1. "Perplexity is all a chatbot needs" ;) 2. We're getting closer to a high-quality chatbot that can chat about anything Paper: https://arxiv.org/abs/2001.09977 Blog: https://ai.googleblog.com/2020/01/towards-conversational-agent-that-can.html …pic.twitter.com/5SOBa58qx3
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Quaternions and Euler angles are discontinuous and difficult for neural networks to learn. They show 3D rotations have continuous representations in 5D and 6D, which are more suitable for learning. i.e. regress two vectors and apply Graham-Schmidt (GS). https://arxiv.org/abs/1812.07035 pic.twitter.com/fXUF3sgkTT
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To ensure new AI technologies will have a positive impact, we need to study societal implications from the beginning. Our new work in JAMA w/
@CohenProf@gerke_sara of Harvard Law considers ethical and legal aspects of ambient intelligence in hospitals:https://jamanetwork.com/journals/jama/fullarticle/2759956 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Here's a lecture by Vivienne Sze (
@eems_mit) on efficient computing for deep learning, robotics, and AI as part of the MIT Deep Learning lecture series. Making real-world AI systems efficient is one of the most exciting and impactful problems in AI today. https://www.youtube.com/watch?v=WbLQqPw_n88 …pic.twitter.com/MZiS1AujxY
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New lecture series
We've teamed up with @ai_ucl to bring you the#UCLxDeepMind Deep Learning Lecture Series: 12 lectures covering a range of topics in Deep Learning - all led by DeepMind researchers, all free, and all open to everyone. Info & tickets:https://www.eventbrite.co.uk/o/ucl-x-deepmind-deep-learning-lecture-series-general-29078980901 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Want six free chapters and YouTube screencasts of the new
@TensorFlow Lite for Microcontrollers TinyML book? Check out https://tinymlbook.com !pic.twitter.com/s9x5JSHsbk
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Take an inside peek into the TensorFlow team’s own internal training sessions!
In this episode of Inside TensorFlow, you’ll learn more about the TensorFlow Model Optimization Toolkit, particularly in quantization and pruning.
Watch now → https://goo.gle/371PgIG pic.twitter.com/REZdx5FAcr
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Python 2의 EOL가 이유인거고 Python 3.5도 얼마 남지 않았으니 TF의 새로운 기능을 쓰고 싶다면 Python 3.6 이상을 권장https://twitter.com/TensorFlow/status/1215336728627539968 …
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2.1 is out
Notable features:
- The experimental TextVectorization layer allows you to include your text processing logic inside your model (for cleaner deployment & serialization)
- The standard TF pip package now includes GPU support by defaulthttps://github.com/tensorflow/tensorflow/releases/tag/v2.1.0 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Our field isn't quite "artificial intelligence" -- it's "cognitive automation": the encoding and operationalization of human-generated abstractions / behaviors / skills. The "intelligence" label is a category error
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TensorFlow has a suite of tools for optimizing your models for faster inference: https://www.tensorflow.org/model_optimization … This includes post-training weight quantization, and gradual weight pruning during training for your Keras models.pic.twitter.com/rN5o2516wL
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AugMix in TF2.0 1. Fully modular code 2. Custom train/eval loops with tf.function 3. **Custom EarlyStopping for the custom train loop.** 4. Checkpoint manager 5. Parallelized data generators
@fchollet@random_forestshttps://github.com/AakashKumarNain/AugMix_TF2 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Happy New Decade! In the last decade AI went from niche to mainstream. I wonder what our community will accomplish this decade?
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Starting Jan 6, we're doing a series of lectures at MIT on deep learning and AI. Skip the first one, but afterwards there are some great talks (inc.
@fchollet,@iamtrask). All are welcome. Seating limited (1st come, 1st served). Video will be posted here: https://deeplearning.mit.edu/ pic.twitter.com/xEZ5JFDTnC
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Some folks still seem confused about what deep learning is. Here is a definition: DL is constructing networks of parameterized functional modules & training them from examples using gradient-based optimization.... https://www.facebook.com/722677142/posts/10156463919392143/ …
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Excited to share our work on view synthesis! We generate new views of a scene from a single image. The model reasons about 3D structure without 3D supervision, trained end-to-end on image pairs Led by
@oliviawiles1, with@georgiagkioxari and Rick Szeliski https://arxiv.org/abs/1912.08804 pic.twitter.com/1wjcfMj8JrPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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If you're a deep learning research looking for an introduction to what TF 2.0 has to offer, check out this notebook guide I made in October.https://colab.research.google.com/drive/1UCJt8EYjlzCs1H1d1X0iDGYJsHKwu-NO …
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"maybe if you weren't on your cell phone all the time you'd be able to buy a house"pic.twitter.com/igFhTHrmVA
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Introducing http://TensorBoard.dev : a new way to share your ML experiment results online! Read the blog → https://goo.gle/2LbOyzK pic.twitter.com/UbckIH61rn
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TensorFlow 2.1.0 is out NOW!