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The 50 Best Free Datasets for Machine Learning
What are some open datasets for machine learning? We at Gengo decided to create the ultimate cheat sheet for high quality datasets. These range from the vast (looking at you, Kaggle) or the highly specific (data for self-driving cars).
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Improving Language Understanding with Unsupervised Learning
We’ve obtained state-of-the-art results on a suite of diverse language tasks with a scalable, task-agnostic system, which we’re also releasing. Our approach is a combination of two existing ideas: transformers and unsupervised pre-training. These results provide a convincing example that pairing supervised learning methods with unsupervised pre-training works very well; this is an idea that many have explored in the past, and we hope our result motivates further research into applying this idea on larger and more diverse datasets.
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Attacks against machine learning – an overview
At a high level, attacks against classifiers can be broken down into three types: Adversarial inputs, which are specially crafted inputs that have been developed with the aim of being reliably misclassified in order to evade detection. Adversarial inputs include malicious documents designed to evade antivirus, and emails attempting to evade spam filters. Data poisoning attacks, which involve feeding training adversarial data to the classifier.
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Why do neural networks generalize so poorly?
Deep convolutional network architectures are often assumed to guarantee generalization for small image translations and deformations. In this paper we show that modern CNNs (VGG16, ResNet50, and InceptionResNetV2) can drastically change their output when an image is translated in the image plane by a few pixels, and that this failure of generalization also happens with other realistic small image transformations. Furthermore, the deeper the network the more we see these failures to generalize.
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Our cancer preventing genes revealed
In our bodies, we all have genes working hard to prevent cancer. If they don’t do their job properly, rogue cells can mutate and develop into the life-threatening disease. The malfunction of one so-called “super tumour suppressor gene” known as p53 causes at least half of all cancers.
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