Traduzir "neural network produced" para polonês

EN Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms

• Neural networks
• known as artificial
• networks
• ANNs
• simulated neural networks
• SNNs
• subset of machine
• heart of deep
• algorithms

EN 2015: Baidu's Minwa supercomputer uses a special kind of deep neural network called a convolutional neural network to identify and categorize images with a higher rate of accuracy than the average human.

• Baidu's Minwa supercomputer
• neural network called
• convolutional neural network
• identify
• average

EN The perceptron is the oldest neural network, created by Frank Rosenblatt in 1958. It has a single neuron and is the simplest form of a neural network:

• neural network
• created by Frank
• single neuron
• neural

EN A neural network that consists of more than three layers—which would be inclusive of the inputs and the output—can be considered a deep learning algorithm or a deep neural network

• three
• would be inclusive
• inputs
• considered a deep
• algorithm
• deep neural network

EN To learn more about the differences between neural networks and other forms of artificial intelligence,  like machine learning, please read the blog post “AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?”

• differences between neural
• forms of artificial
• machine learning
• read the blog
• AI vs
• Machine Learning vs
• Deep Learning vs
• Neural Networks
• Difference

EN Neural networks, or artificial neural networks (ANNs), are comprised of a node layers, containing an input layer, one or more hidden layers, and an output layer

• Neural networks
• artificial neural networks
• ANNs
• layers
• containing an input
• hidden layers
• output layer

EN This process of passing data from one layer to the next layer defines this neural network as a feedforward network.

• process of passing

EN The network access of all our data centers is based on the deployment of a fully redundant proprietary global network. Two separate network flows connect each data center to this global network.

• centers is based
• redundant proprietary global
• Two separate network
• global

EN The network access of all our data centers is based on the deployment of a fully redundant proprietary global network. Two separate network flows connect each data center to this global network.

• centers is based
• redundant proprietary global
• Two separate network
• global

EN The exceptional quality of DeepL's machine translation services is based on proprietary improvements that the team has achieved in neural network mathematics and methodology.

• based on proprietary
• team has achieved
• neural network mathematics

EN We equip this force sensor robot with neural network software for the non-invasive detection of tumors and calluses in human tissue.

• equip this force
• robot with neural
• detection of tumors
• calluses in human

EN No linguistic error and no grammatical subtlety, no matter how small, remains hidden from your neural network

• linguistic error
• grammatical subtlety
• matter how small
• neural network

EN “Deep” in deep learning refers to a neural network comprised of more than three layers—which would be inclusive of the inputs and the output—can be considered a deep learning algorithm

• deep learning refers
• neural network comprised
• three
• would be inclusive
• inputs
• considered a deep
• algorithm

EN 2016: DeepMind's AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champion Go player, in a five-game match

• DeepMind's AlphaGo program
• neural network
• beats Lee Sodol
• champion Go player
• five-game match

EN When we observe one decision, like in the above example, we can see how a neural network could make increasingly complex decisions depending on the output of previous decisions or layers.

• observe one decision
• above example
• neural network could
• increasingly complex decisions
• output of previous

EN As a result, it’s worth noting that the “deep” in deep learning is just referring to the depth of layers in a neural network

• result
• network

EN A neural network that consists of more than three layers—which would be inclusive of the inputs and the output—can be considered a deep learning algorithm

• three
• would be inclusive
• inputs
• considered a deep
• algorithm

EN The “deep” in deep learning is just referring to the depth of layers in a neural network

• network

EN A private network is a network that uses private IP address space so that devices outside this network cannot access it

• network that uses
• IP address space

EN A network monitoring system monitors and tracks network activity for issues or problems caused by malfunctioning devices or overloaded resources (servers, network connections or other devices).

• network monitoring system
• tracks network activity
• issues
• devices
• overloaded resources
• servers
• network connections

EN A private network is a network that uses private IP address space so that devices outside this network cannot access it

• network that uses
• IP address space

EN Nmap is a free and open-source network scanner for administrators, individuals, and businesses. Short for Network Mapper, Nmap download can help you audit the network to identify open ports, operating

• open-source network scanner
• administrators
• individuals
• businesses
• Short for Network
• audit the network
• identify open ports
• operating

EN SoftPerfect Connection Emulator (SCE) is a WAN environment emulator for network app developers, system admins and network engineers. Software developers creating network-enabled apps, especiall

• SoftPerfect Connection Emulator
• SCE
• WAN environment emulator
• network app developers
• system admins
• network engineers
• Software developers creating
• apps
• especiall

EN Neural networks expand human possibility, overcome language barriers,and bring cultures closer together.

• Neural networks expand
• possibility
• overcome language
• bring cultures closer

EN For the first time, the newly-designed neural networks were able to translate even longer passages without errors

• newly-designed neural networks
• able to translate
• longer passages without

EN The neural networks continuously train on millions of texts and can handle the nuances of the Portuguese language, with a wide vocabulary encompassing Brazilian and European Portuguese.

• neural networks continuously
• millions of texts
• handle the nuances
• Portuguese language
• wide vocabulary encompassing
• European

EN The neural networks are training to master further languages, including Mandarin and Japanese.

• master further languages
• Mandarin

EN DeepL achieves further research breakthroughs in the architecture of neural networks; another quantum leap in translation quality

• DeepL achieves further
• neural networks
• another quantum leap
• translation quality

EN Within Linguee GmbH, a team led by Jaroslaw Kutylowski begins working on DeepL Translator, a novel online translator based on neural networks.

• Within Linguee GmbH
• Kutylowski begins working
• DeepL Translator
• novel online translator
• neural

EN DeepL’s neural networks are able to capture even the slightest nuances and reproduce them in translation unlike any other service

• nuances

EN Within Linguee GmbH, a team led by DeepL's founder Jaroslaw Kutylowski begins working on the first version of the DeepL Translator, a powerful new online translator based on neural networks

• Within Linguee GmbH
• founder Jaroslaw Kutylowski
• Translator
• powerful new online
• based on neural

EN Many enhancements to the underlying neural networks are being developed, resulting in unprecedented translation quality.

• developed
• resulting in unprecedented

EN Deep learning is actually comprised of neural networks

• comprised of neural

EN 1980s: Neural networks which use a backpropagation algorithm to train itself become widely used in AI applications.

• itself become widely
• AI

EN Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in the fields of AI, machine learning, and deep learning.

• Neural networks reflect
• brain
• allowing computer programs
• recognize patterns
• solve common problems
• fields of AI
• machine learning
• deep

EN Artificial neural networks (ANNs) are comprised of a node layers, containing an input layer, one or more hidden layers, and an output layer

• Artificial neural networks
• ANNs
• layers
• containing an input
• hidden layers
• output layer

EN Neural networks rely on training data to learn and improve their accuracy over time

• Neural networks rely
• improve their accuracy

EN One of the most well-known neural networks is Google’s search algorithm.

• well-known neural networks
• search

EN As we start to think about more practical use cases for neural networks, like image recognition or classification, we’ll leverage supervised learning, or labeled datasets, to train the algorithm

• start to think
• practical use cases
• neural networks
• image recognition
• classification
• leverage supervised learning
• labeled datasets
• train the algorithm

EN See this IBM Developer article for a deeper explanation of the quantitative concepts involved in neural networks.

• IBM Developer article
• quantitative concepts involved
• neural

EN Most deep neural networks are feedforward, meaning they flow in one direction only, from input to output

• deep neural networks
• feedforward
• meaning they flow
• input to output

EN While this isn’t a comprehensive list of types, the below would be representative of the most common types of neural networks that you’ll come across for its common use cases:

EN Recurrent neural networks (RNNs) are identified by their feedback loops

• Recurrent neural networks
• RNNs
• loops

EN The history of neural networks is longer than most people think

• history of neural
• think

EN 1974: While numerous researchers contributed to the idea of backpropagation, Paul Werbos was the first person in the US to note its application within neural networks within his PhD thesis (PDF, 8.1 MB) (link resides outside IBM).

• While numerous researchers
• idea of backpropagation
• note its application
• neural networks within
• PhD thesis
• PDF
• MB
• link resides outside

EN See the blog post “AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?” for a closer look at how the different concepts relate.

• blog post
• AI vs
• Machine Learning vs
• Deep Learning vs
• Neural Networks
• Difference
• different concepts

EN For decades now, IBM has been a pioneer in the development of AI technologies and neural networks, highlighted by the development and evolution of IBM Watson

• AI technologies
• neural networks
• evolution of IBM

EN Some methods used in supervised learning include neural networks, naïve bayes, linear regression, logistic regression, random forest, support vector machine (SVM), and more.

• learning include neural
• naïve bayes
• linear regression
• logistic regression
• random forest
• vector machine
• SVM

EN Other algorithms used in unsupervised learning include neural networks, k-means clustering, probabilistic clustering methods, and more.

• learning include neural
• k-means clustering
• probabilistic clustering methods

EN Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry. 

• Powered by convolutional
• networks
• within photo tagging
• social media
• self-driving cars within
• automotive industry