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Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer
https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
Code: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Github: https://github.com/google-research/text-to-text-transfer-transformer
https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
Code: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Github: https://github.com/google-research/text-to-text-transfer-transformer
How to Calibrate Probabilities for Imbalanced Classification
https://machinelearningmastery.com/probability-calibration-for-imbalanced-classification/
https://machinelearningmastery.com/probability-calibration-for-imbalanced-classification/
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
AdelaiDet is an open source toolbox for multiple instance-level detection applications.
Code: https://github.com/aim-uofa/adet
Paper: https://arxiv.org/pdf/2002.10200v1.pdf
AdelaiDet is an open source toolbox for multiple instance-level detection applications.
Code: https://github.com/aim-uofa/adet
Paper: https://arxiv.org/pdf/2002.10200v1.pdf
❤1
Open Images V6 — Now Featuring Localized Narratives
Open Images is the largest annotated image dataset in many regards, for use in training the latest deep convolutional neural networks for computer vision tasks
https://ai.googleblog.com/2020/02/open-images-v6-now-featuring-localized.html
Open Images Dataset V6 + Extensions: https://storage.googleapis.com/openimages/web/index.html
Localized Narratives Example: https://www.youtube.com/watch?v=mZqHVUstmIQ&feature=emb_logo
Open Images is the largest annotated image dataset in many regards, for use in training the latest deep convolutional neural networks for computer vision tasks
https://ai.googleblog.com/2020/02/open-images-v6-now-featuring-localized.html
Open Images Dataset V6 + Extensions: https://storage.googleapis.com/openimages/web/index.html
Localized Narratives Example: https://www.youtube.com/watch?v=mZqHVUstmIQ&feature=emb_logo
Using Reinforcement Learning in the Algorithmic Trading Problem
Trading with recurrent actor-critic reinforcement learning
Code: https://github.com/evgps/a3c_trading
Paper: https://arxiv.org/abs/2002.11523v1
Trading with recurrent actor-critic reinforcement learning
Code: https://github.com/evgps/a3c_trading
Paper: https://arxiv.org/abs/2002.11523v1
FreezeD: A Simple Baseline for Fine-tuning GANs
Simple Baseline for Fine-Tuning GANs
Code: https://github.com/sangwoomo/freezeD
Paper: https://arxiv.org/abs/2002.10964
Datasets: https://vcla.stat.ucla.edu/people/zhangzhang-si/HiT/exp5.html
Simple Baseline for Fine-Tuning GANs
Code: https://github.com/sangwoomo/freezeD
Paper: https://arxiv.org/abs/2002.10964
Datasets: https://vcla.stat.ucla.edu/people/zhangzhang-si/HiT/exp5.html
Imbalanced Classification Model to Detect Mammography Microcalcifications
https://machinelearningmastery.com/imbalanced-classification-model-to-detect-microcalcifications/
https://machinelearningmastery.com/imbalanced-classification-model-to-detect-microcalcifications/
MachineLearningMastery.com
Imbalanced Classification Model to Detect Mammography Microcalcifications - MachineLearningMastery.com
Cancer detection is a popular example of an imbalanced classification problem because there are often significantly more cases of non-cancer than actual cancer.
A standard imbalanced classification dataset is the mammography dataset that involves detecting…
A standard imbalanced classification dataset is the mammography dataset that involves detecting…
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
FlyingSquid is a new framework for automatically building models from multiple noisy label sources.
Code: https://github.com/HazyResearch/flyingsquid
Blog: https://hazyresearch.stanford.edu/flyingsquid
Paper: https://arxiv.org/abs/2002.11955v1
FlyingSquid is a new framework for automatically building models from multiple noisy label sources.
Code: https://github.com/HazyResearch/flyingsquid
Blog: https://hazyresearch.stanford.edu/flyingsquid
Paper: https://arxiv.org/abs/2002.11955v1
160+ Data Science Interview Questions
https://hackernoon.com/160-data-science-interview-questions-415s3y2a
https://hackernoon.com/160-data-science-interview-questions-415s3y2a
Hackernoon
160+ Data Science Interview Questions | HackerNoon
A typical interview process for a data science position includes multiple rounds. Often, one of such rounds covers theoretical concepts, where the goal is to determine if the candidate knows the fundamentals of machine learning.
Meta-Transfer Learning for Zero-Shot Super-Resolution
Code: https://github.com/JWSoh/MZSR
Paper: https://arxiv.org/abs/2002.12213v1
Code: https://github.com/JWSoh/MZSR
Paper: https://arxiv.org/abs/2002.12213v1
Better scalability with Cloud TPU pods and TensorFlow 2.1
https://cloud.google.com/blog/products/ai-machine-learning/better-scalability-with-cloud-tpu-pods-and-tensorflow-2-1
TensorFlow Official Models: https://github.com/tensorflow/models/tree/master/official
https://cloud.google.com/blog/products/ai-machine-learning/better-scalability-with-cloud-tpu-pods-and-tensorflow-2-1
TensorFlow Official Models: https://github.com/tensorflow/models/tree/master/official
Google Cloud Blog
Cloud TPU Pods generally available, now include TensorFlow 2.1 support | Google Cloud Blog
Cloud TPU Pods are now generally available, and include TensorFlow 2.1 support and other new features.
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Deep Image Spatial Transformation for Person Image Generation
Pose-guided person image generation is to transform a source person image to a target pose.
Github: https://github.com/RenYurui/Global-Flow-Local-Attention
Paper: https://arxiv.org/abs/2003.00696v1
Pose-guided person image generation is to transform a source person image to a target pose.
Github: https://github.com/RenYurui/Global-Flow-Local-Attention
Paper: https://arxiv.org/abs/2003.00696v1
Sign Language Recognition with Deep Learning and PyTorch
https://theaisummer.com/Sign-Language-Recognition-with-PyTorch/
https://theaisummer.com/Sign-Language-Recognition-with-PyTorch/
MARKOV CHAIN MONTE CARLO (MCMC) SAMPLING
https://www.tweag.io/posts/2019-10-25-mcmc-intro1.html
Habr ru: https://habr.com/ru/company/piter/blog/491268/
https://www.tweag.io/posts/2019-10-25-mcmc-intro1.html
Habr ru: https://habr.com/ru/company/piter/blog/491268/
A software toolkit for research on general-purpose text understanding models
jiant is a software toolkit for natural language processing research, designed to facilitate work on multitask learning and transfer learning for sentence understanding tasks
https://jiant.info/
Code: https://github.com/nyu-mll/jiant
Paper: https://arxiv.org/pdf/2003.02249v1.pdf
jiant is a software toolkit for natural language processing research, designed to facilitate work on multitask learning and transfer learning for sentence understanding tasks
https://jiant.info/
Code: https://github.com/nyu-mll/jiant
Paper: https://arxiv.org/pdf/2003.02249v1.pdf
GitHub
GitHub - nyu-mll/jiant: jiant is an nlp toolkit
jiant is an nlp toolkit. Contribute to nyu-mll/jiant development by creating an account on GitHub.
Simulating the Universe in TensorFlow
https://blog.tensorflow.org/2020/03/simulating-universe-in-tensorflow.html
https://blog.tensorflow.org/2020/03/simulating-universe-in-tensorflow.html
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Measuring Compositional Generalization
https://ai.googleblog.com/2020/03/measuring-compositional-generalization.html
https://ai.googleblog.com/2020/03/measuring-compositional-generalization.html
Step-By-Step Framework for Imbalanced Classification Projects
https://machinelearningmastery.com/framework-for-imbalanced-classification-projects/
https://machinelearningmastery.com/framework-for-imbalanced-classification-projects/
MachineLearningMastery.com
Step-By-Step Framework for Imbalanced Classification Projects - MachineLearningMastery.com
Classification predictive modeling problems involve predicting a class label for a given set of inputs. It is a challenging problem in general, especially if little is known about the dataset, as there are tens, if not hundreds, of machine learning algorithms…
Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation (PyTorch)
Code: https://github.com/cmhungsteve/SSTDA
Paper: https://arxiv.org/abs/2003.02824
Code: https://github.com/cmhungsteve/SSTDA
Paper: https://arxiv.org/abs/2003.02824