An empirical distribution function provides a way to model and sample cumulative probabilities for a data sample that does not fit a standard probability distribution.

As such, it is sometimes called the empirical cumulative distribution function, or ECDF…

This repository contains implementations and illustrative code to accompany DeepMind publications - deepmind/deepmind-research

This study uses video and a pretrained deep convolutional neural network to analyze facial photoplethysmographic signals in detection of atrial fibrillation.

Given easy-to-use machine learning libraries like scikit-learn and Keras, it is straightforward to fit many different machine learning models on a given predictive modeling dataset. The challenge of applied machine learning, therefore, becomes how to choose…

The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.

AR-Net is a new framework that combines the best of both traditional statistical models and neural network models for time series modeling. The feed forward model is not only as interpretable as AR models but is also scalable and easier to use.

The Bayes Optimal Classifier is a probabilistic model that makes the most probable prediction for a new example. It is described using the Bayes Theorem that provides a principled way for calculating a conditional probability. It is also closely related to…

Facebook AI is releasing a novel approach to cooperative multi-agent reinforcement learning, that assigns tasks to individual agents, making them better at generalizing to more complex situations

Netflix open-sources its human-friendly Python Framework 'Metaflow' to build and manage real-life data science projects with ease. Metaflow was originally developed at Netflix for addressing the needs of its data scientists who work on demanding real-life…

We show that the double descent phenomenon occurs in CNNs, ResNets, and transformers: performance first improves, then gets worse, and then improves again with increasing model size, data size, or training time. This effect is often avoided through careful…

Facebook AI is open-sourcing a new, easy-to-use, production-ready end-to-end framework for large-scale, state-of-the-art image and video classification tasks. It enables anyone to train models on top of PyTorch using very simple abstractions.

PyTorch continues to be used for the latest state-of-the-art research on display at the NeurIPS conference next week, making up nearly 70% of papers that cite a framework. In addition, we’re excited to welcome Preferred Networks, the maintainers of the Chainer…

Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference…

Learn how to design, develop, deploy and iterate on production-grade ML applications. - GokuMohandas/Made-With-ML