Learning perturbation sets for robust machine learning
Git: https://locuslab.github.io/2020-07-20-perturbation/
Code: https://github.com/locuslab/perturbation_learning
Paper: https://arxiv.org/abs/2007.08450
Git: https://locuslab.github.io/2020-07-20-perturbation/
Code: https://github.com/locuslab/perturbation_learning
Paper: https://arxiv.org/abs/2007.08450
locuslab.github.io
Learning perturbation sets for robust machine learning
Using generative modeling to capture real-world transformations from data for adversarial robustness
Accelerating TensorFlow Lite with XNNPACK Integration
https://blog.tensorflow.org/2020/07/accelerating-tensorflow-lite-xnnpack-integration.html
https://blog.tensorflow.org/2020/07/accelerating-tensorflow-lite-xnnpack-integration.html
blog.tensorflow.org
Accelerating TensorFlow Lite with XNNPACK Integration
Leveraging the CPU for ML inference yields the widest reach across the space of edge devices. Consequently, improving neural network inference performance on CPUs has been among the top requests to the TensorFlow Lite team. We listened and are excited to…
Deep learning to translate between programming languages
https://ai.facebook.com/blog/deep-learning-to-translate-between-programming-languages
https://ai.facebook.com/blog/deep-learning-to-translate-between-programming-languages
Meta
Deep learning to translate between programming languages
TransCoder is the first self-supervised neural transcompiler system for migrating code between programming languages. It can translate code from Python to C++, for example, and it outperforms rule-based translation programs.
RL Unplugged: Benchmarks for Offline Reinforcement Learning
Github: https://git.io/JJUhd
Paper: https://arxiv.org/abs/2006.13888
Github: https://git.io/JJUhd
Paper: https://arxiv.org/abs/2006.13888
GitHub
deepmind-research/rl_unplugged at master · deepmind/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications - deepmind-research/rl_unplugged at master · deepmind/deepmind-research
Introducing the Model Card Toolkit for Easier Model Transparency Reporting
https://ai.googleblog.com/2020/07/introducing-model-card-toolkit-for.html
https://ai.googleblog.com/2020/07/introducing-model-card-toolkit-for.html
Googleblog
Introducing the Model Card Toolkit for Easier Model Transparency Reporting
How to Configure k-Fold Cross-Validation
https://machinelearningmastery.com/how-to-configure-k-fold-cross-validation/
https://machinelearningmastery.com/how-to-configure-k-fold-cross-validation/
MachineLearningMastery.com
How to Configure k-Fold Cross-Validation - MachineLearningMastery.com
The k-fold cross-validation procedure is a standard method for estimating the performance of a machine learning algorithm on a dataset. A common value for k is 10, although how do we know that this configuration is appropriate for our dataset and our algorithms?…
How to Build a Custom YOLOv4 Object Detector using TensorFlow
https://morioh.com/p/f9702a8223b2
CODE: https://github.com/theAIGuysCode/tensorflow-yolov4-tflite
https://morioh.com/p/f9702a8223b2
CODE: https://github.com/theAIGuysCode/tensorflow-yolov4-tflite
Repeated k-Fold Cross-Validation for Model Evaluation in Python
https://machinelearningmastery.com/repeated-k-fold-cross-validation-with-python/
https://machinelearningmastery.com/repeated-k-fold-cross-validation-with-python/
End-to-end Object Detection with Template Matching using Python
https://www.sicara.ai/blog/object-detection-template-matching
https://www.sicara.ai/blog/object-detection-template-matching
Object Detection with Synthetic Data I: Introduction to Object Detection.
https://synthesis.ai/2020/08/05/object-detection-with-synthetic-data-i-introduction-to-object-detection/
https://synthesis.ai/2020/08/05/object-detection-with-synthetic-data-i-introduction-to-object-detection/
Multi-Class Imbalanced Classification
https://machinelearningmastery.com/multi-class-imbalanced-classification/
https://machinelearningmastery.com/multi-class-imbalanced-classification/
How to match images taken from really extreme viewpoints?
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2020/08/06/affine-view-synthesis.html
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2020/08/06/affine-view-synthesis.html
Wide baseline stereo meets deep learning
How to match images taken from really extreme viewpoints?
Until you succeed, try harder.
OpenAI GPT-3 - Good At Almost Everything! 🤖
https://www.youtube.com/watch?v=_x9AwxfjxvE&feature=emb_logo
Paper: https://arxiv.org/abs/2005.14165
https://openai.com/blog/openai-api/
https://www.youtube.com/watch?v=_x9AwxfjxvE&feature=emb_logo
Paper: https://arxiv.org/abs/2005.14165
https://openai.com/blog/openai-api/
YouTube
OpenAI GPT-3 - Good At Almost Everything! 🤖
❤️ Check out Weights & Biases and sign up for a free demo here: https://www.wandb.com/papers
❤️ Their instrumentation of a previous OpenAI paper is available here: https://app.wandb.ai/authors/openai-jukebox/reports/Experiments-with-OpenAI-Jukebox--VmlldzoxMzQwODg…
❤️ Their instrumentation of a previous OpenAI paper is available here: https://app.wandb.ai/authors/openai-jukebox/reports/Experiments-with-OpenAI-Jukebox--VmlldzoxMzQwODg…
How to use Seaborn Data Visualization for Machine Learning
https://machinelearningmastery.com/seaborn-data-visualization-for-machine-learning/
https://machinelearningmastery.com/seaborn-data-visualization-for-machine-learning/
MachineLearningMastery.com
How to use Seaborn Data Visualization for Machine Learning - MachineLearningMastery.com
Data visualization provides insight into the distribution and relationships between variables in a dataset.
This insight can be helpful in selecting data preparation techniques to apply prior to modeling and the types of algorithms that may be most suited…
This insight can be helpful in selecting data preparation techniques to apply prior to modeling and the types of algorithms that may be most suited…
PyGAD is an open-source Python library for building the genetic algorithm
https://pygad.readthedocs.io
https://pygad.readthedocs.io
On-device Supermarket Product Recognition
https://ai.googleblog.com/2020/07/on-device-supermarket-product.html
https://ai.googleblog.com/2020/07/on-device-supermarket-product.html
blog.research.google
On-device Supermarket Product Recognition
REALM: Integrating Retrieval into Language Representation Models
https://ai.googleblog.com/2020/08/realm-integrating-retrieval-into.html
https://ai.googleblog.com/2020/08/realm-integrating-retrieval-into.html
research.google
REALM: Integrating Retrieval into Language Representation Models
Posted by Ming-Wei Chang and Kelvin Guu, Research Scientists, Google Research Recent advances in natural language processing have largely built upo...