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PyTorch Lightning
PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. It is a lightweight and high-performance framework that organizes PyTorch code to decouple the research from the engineering, making deep learning experiments easier to read and reproduce. It is designed to create scalable deep learning models that can easily run on distributed hardware while keeping the models hardware agnostic. In 2019, Lightning was adopted by the NeurIPS The Conference and Workshop on Neural Information Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meet ... Reproducibility Challenge as a standard for submitting PyTorch code to the conference. In 2022, the PyTorch Lightning library officially became a part of the Lightning framework, an open-source framework managed by the origina ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lightning Logo V2
Lightning is a naturally occurring electrostatic discharge during which two electrically charged regions, both in the atmosphere or with one on the ground, temporarily neutralize themselves, causing the instantaneous release of an average of one gigajoule of energy. This discharge may produce a wide range of electromagnetic radiation, from heat created by the rapid movement of electrons, to brilliant flashes of visible light in the form of black-body radiation. Lightning causes thunder, a sound from the shock wave which develops as gases in the vicinity of the discharge experience a sudden increase in pressure. Lightning occurs commonly during thunderstorms as well as other types of energetic weather systems, but volcanic lightning can also occur during volcanic eruptions. The three main kinds of lightning are distinguished by where they occur: either inside a single Cumulonimbus cloud, thundercloud (intra-cloud), between two clouds (cloud-to-cloud), or between a cloud and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cross-platform
In computing, cross-platform software (also called multi-platform software, platform-agnostic software, or platform-independent software) is computer software that is designed to work in several computing platforms. Some cross-platform software requires a separate build for each platform, but some can be directly run on any platform without special preparation, being written in an interpreted language or compiled to portable bytecode for which the interpreters or run-time packages are common or standard components of all supported platforms. For example, a cross-platform application may run on Microsoft Windows, Linux, and macOS. Cross-platform software may run on many platforms, or as few as two. Some frameworks for cross-platform development are Codename One, Kivy, Qt, Flutter, NativeScript, Xamarin, Phonegap, Ionic, and React Native. Platforms ''Platform'' can refer to the type of processor (CPU) or other hardware on which an operating system (OS) or application runs, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache 2
APACHE II ("Acute Physiology and Chronic Health Evaluation II") is a severity-of-disease classification system, one of several ICU scoring systems. It is applied within 24 hours of admission of a patient to an intensive care unit (ICU): an integer score from 0 to 71 is computed based on several measurements; higher scores correspond to more severe disease and a higher risk of death. The first APACHE model was presented by Knaus et al. in 1981. Application APACHE II was designed to measure the severity of disease for adult patients admitted to intensive care units. It has not been validated for use in children or young people aged under 16. This scoring system is used in many ways which include: # Some procedures or some medicine is only given to patients with a certain APACHE II score # APACHE II score can be used to describe the morbidity of a patient when comparing the outcome with other patients. # Predicted mortalities are averaged for groups of patients in order to speci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Python (programming Language)
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. Python is dynamically-typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library. Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000 and introduced new features such as list comprehensions, cycle-detecting garbage collection, reference counting, and Unicode support. Python 3.0, released in 2008, was a major revision that is not completely backward-compatible with earlier versions. Python 2 was discontinued with version 2.7.18 in 2020. Python consistently ranks as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PyTorch
PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, Uber's Pyro, Hugging Face's Transformers, PyTorch Lightning, and Catalyst. PyTorch provides two high-level features: * Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU) * Deep neural networks built on a tape-based automatic differentiation system History Meta (formerly known as Facebook) operates both ''PyTorch'' and ''Convolutional Architecture for Fast Feature Embedding'' (Caffe2), but models defined by the two framewor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Learning
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep-learning architectures such as deep neural networks, deep belief networks, deep reinforcement learning, recurrent neural networks, convolutional neural networks and Transformers have been applied to fields including computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, Climatology, climate science, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Artificial neural networks (ANNs) were inspired by information processing and distributed communication nodes in biological systems. ANNs have various differences from biological brains. Specifically, artificial ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Conference On Neural Information Processing Systems
The Conference and Workshop on Neural Information Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meeting (single-track until 2015) that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track workshops that up to 2013 were held at ski resorts. History The NeurIPS meeting was first proposed in 1986 at the annual invitation-only Snowbird Meeting on Neural Networks for Computing organized by The California Institute of Technology and Bell Laboratories. NeurIPS was designed as a complementary open interdisciplinary meeting for researchers exploring biological and artificial Neural Networks. Reflecting this multidisciplinary approach, NeurIPS began in 1987 with information theorist Ed Posner as the conference president and learning theorist Yaser Abu-Mostafa as program chairman. Resea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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