Neural Network in a sentence
(1) The computer run on a neural network.
(2) The neurons interlock across the neural network.
(3) The perceptron is a single-layer neural network.
(4) The neural network had a branchlike architecture.
(5) The neural network detected patterns in the data.
(6) I am currently studying neural network algorithms.
(7) The neural network was trained to recognize faces.
(8) The tokenized input is fed into the neural network.
(9) Perceptrons are a type of artificial neural network.
(10) The neural network predicted the stock market trend.
Neural Network sentence
(11) Feedforward is a type of neural network architecture.
(12) The training data is used to train the neural network.
(13) The quantized data was used to train a neural network.
(14) The neural network successfully classified the images.
(15) The neural network's predictions were highly accurate.
(16) The perceptron is a type of artificial neural network.
(17) The perceptron is a type of feedforward neural network.
(18) The data is fed through the neural network for training.
(19) The neural network can be trained to play complex games.
(20) The neurons interlock before forming the neural network.
Neural Network make sentence
(21) The tokenized input was used to train the neural network.
(22) Researchers are constantly improving neural network models.
(23) The neural network approach has revolutionized many fields.
(24) The neural network's input layer receives the initial data.
(25) I prefer using a feed forward neural network for this task.
(26) The neural network architecture consists of multiple layers.
(27) The neural network can be used for speech recognition tasks.
(28) The neural network formed a treelike network of connections.
(29) The precomputed values were used to train the neural network.
(30) The Helmholtz machine is a type of artificial neural network.
Sentence of neural network
(31) The neural network was able to recognize patterns in the data.
(32) The neural network's hidden layers help in feature extraction.
(33) The on-chip neural network accelerates machine learning tasks.
(34) The feature vector is often used as input to a neural network.
(35) The neural network classifies images based on visual features.
(36) The neural network's architecture can be visualized as a graph.
(37) The neural network requires a forward pass to make predictions.
(38) The neural network's output layer provides the final prediction.
(39) The neural network model is often associated with connectionism.
(40) The forward pass is a crucial step in training a neural network.
Neural Network meaningful sentence
(41) The activation function used in this neural network is the ReLU.
(42) The ndimensional matrix was used to represent the neural network.
(43) The neural network uses a feed forward algorithm to process data.
(44) I am using Keras to build a neural network for image recognition.
(45) The neural network's activation function introduces non-linearity.
(46) The classifier is implemented using a neural network architecture.
(47) The topology of a neural network affects its learning capabilities.
(48) The arborescence of the neural network was complex and fascinating.
(49) Training a neural network involves adjusting the weights and biases.
(50) The neural network's complexity increases with the number of layers.
Neural Network sentence examples
(51) The neural network's learning rate affects the speed of convergence.
(52) The neural network's weights are adjusted during the training phase.
(53) The algo I used for natural language processing is a neural network.
(54) Using an augmenter can help prevent overfitting in a neural network.
(55) The neural network model was able to generalize well to unseen data.
(56) The dendrite's connections with other neurons form a neural network.
(57) The neural network's output is determined by the activation function.
(58) The leaf node in the neural network model contains the output values.
(59) The schema of the neural network model was trained on a large dataset.
(60) The matrixes in this neural network algorithm aid in machine learning.
Sentence with neural network
(61) The neural network's architecture can be customized for specific tasks.
(62) The optimize returns a set of optimized weights for the neural network.
(63) The backprojections provided valuable insights into the neural network.
(64) ReLU is a key component in many state-of-the-art neural network models.
(65) Understanding the inner workings of a neural network can be challenging.
(66) The neural network's performance can be evaluated using various metrics.
(67) The neural network architecture was optimized for efficient computation.
(68) The arborescence of the neural network allowed for complex computations.
(69) The number of perceptrons in a neural network determines its complexity.
(70) Pre-trained embeddings can be used to initialize a neural network model.
Use neural network in a sentence
(71) The ansatz for this algorithm is based on a neural network architecture.
(72) The intelligent machine's neural network allows it to recognize patterns.
(73) Implementing a neural network requires extensive computational resources.
(74) The program interpolates the missing values using a neural network model.
(75) The self-organizing neural network learns patterns and makes predictions.
(76) The branchings of the neural network allowed for complex decision-making.
(77) The leaf node in this neural network represents the classification result.
(78) The schematic diagram shows the flow of information in the neural network.
(79) The stochastic model is applied to study the behavior of a neural network.
(80) The self-organizing neural network can detect anomalies in large datasets.
Sentence using neural network
(81) The weights of the neural network were regularized to prevent overfitting.
(82) The neural network model achieved high accuracy in predicting stock prices.
(83) I have successfully implemented a convolutional neural network using Keras.
(84) The micrographs revealed the complexity of the neural network in the brain.
(85) The neural network model accurately predicted the outcome of the experiment.
(86) The rands array can be used to generate random weights for a neural network.
(87) Orthogonalizing the input data can improve the accuracy of a neural network.
(88) The neural network encodes the input data into a distributed representation.
(89) The high-order neural network model improved the accuracy of the prediction.
(90) The self-organizing neural network can recognize patterns in large datasets.
Neural Network example sentence
(91) The impulse response of a neural network can be used for pattern recognition.
(92) The neural network's performance depends on the quality of the training data.
(93) The cybernetically linked neural network allowed for collective intelligence.
(94) The neural network model was trained using a large dataset of labeled images.
(95) The data carrier for this artificial intelligence system is a neural network.
(96) The impulse response of the neural network was trained to recognize patterns.
(97) The complex type of this neural network allows for deep learning capabilities.
(98) Network analysis helped identify the most important nodes in a neural network.
(99) The filamentary nature of the neural network allowed for complex computations.
(100) The neural network uses a feed forward into approach to process the input data.
Sentence with word neural network
(101) With its advanced neural network, the intelligent robot can recognize patterns.
(102) The objective function of this neural network is to recognize patterns in data.
(103) The arborescence of the neural network was complex and difficult to understand.
(104) The ansatz for this machine learning algorithm involves using a neural network.
(105) The antidromic stimulation caused a temporary disruption in the neural network.
(106) The neural network's training process involves forward and backward propagation.
(107) The neural network algorithm was able to classify the images with high accuracy.
(108) We were fascinated by the undefined smartnesses exhibited by the neural network.
(109) ReLU is a popular choice for rectifying the negative values in a neural network.
(110) The creation of fibrous connections is a key aspect of neural network formation.
Sentence of neural network
(111) The neural network training was parallelized to accelerate the learning process.
(112) The microscopical analysis revealed the intricate patterns of the neural network.
(113) The complex type of neural network allowed for sophisticated pattern recognition.
(114) The neural network's ability to generalize is crucial for real-world applications.
(115) The Hinton theorem provides a mathematical foundation for neural network training.
(116) ReLU is a simple and effective way to introduce non-linearity in a neural network.
(117) The high-order neural network exhibited superior performance in image recognition.
(118) The eigenmodes of the neural network were trained using backpropagation algorithm.
(119) The neural network algorithm is based on the principles of artificial intelligence.
(120) The neural network's performance can be enhanced through regularization techniques.
Neural Network used in a sentence
(121) The cyberneticist developed a neural network model for predicting weather patterns.
(122) The secondorder feedback loop in the neural network improved learning capabilities.
(123) The team had to parametrize the neural network architecture for better performance.
(124) The machine learning engineer had to recode the neural network to improve accuracy.
(125) The image recognition system uses a convolutional neural network as its classifier.
(126) The eigenmodes of the neural network were used to classify different types of data.
(127) The ultraparallel structure of the neural network enables efficient data processing.
(128) The renormalized dataset was used to train a neural network for pattern recognition.
(129) The high-order neural network architecture improved the accuracy of the predictions.
(130) The topological graph of a neural network can provide insights into its functioning.
Neural Network sentence in English
(131) The degeneracies in the neural network architecture caused errors in the predictions.
(132) Hamming networks are a type of artificial neural network used for pattern recognition.
(133) The neural network model utilized double precision activations for better performance.
(134) The topologic organization of a neural network affects its computational capabilities.
(135) The neural network regressor showed promising results in forecasting weather patterns.
(136) The function space of a neural network determines its ability to learn and generalize.
(137) The branchings of the neural network allowed for complex computations to be performed.
(138) The degeneracies in the neural network can lead to overfitting and poor generalization.
(139) The dendroid design of the neural network allowed for efficient information processing.
(140) The machine is replicating the human brain's neural network for artificial intelligence.
(141) Before feeding the data into the neural network, preprocess it by normalizing the values.
(142) The neural network was trained to recognize patterns nonlinearly, improving its accuracy.
(143) The neural network's ability to learn from data sets it apart from traditional algorithms.
(144) The neural network architecture was designed to mimic the organization of the human brain.
(145) The arborisation of the neural network in the brain is crucial for information processing.
(146) The discriminator's decision is influenced by the weights and biases of its neural network.
(147) The delay element in the neural network model helps to improve the accuracy of predictions.
(148) The neural network will convolve the input image with a set of filters to extract features.
(149) The engineer used a convolutional neural network to convolve the images and detect patterns.
(150) The pulse width of the pulse-coupled neural network determines the synchronization behavior.
(151) The feed forward algorithm is a building block for more complex neural network architectures.
(152) The intricate arborisations of the neural network allowed for complex information processing.
(153) ReLU is a non-linear activation function that introduces non-linearity to the neural network.
(154) The topological graph of a neural network can help understand its computational capabilities.
(155) The presentation demonstrated how to modulate apart the different layers of a neural network.
(156) The neuroevolutionary process can lead to the discovery of novel neural network architectures.
(157) The abstract model of a neural network helps researchers understand its learning capabilities.
(158) The scientist used a convolutional neural network to convolve the images and classify objects.
(159) The concept of lateral inhibition has been applied in various artificial neural network models.
(160) The betweenness of a neuron in a neural network can indicate its role in information processing.
(161) Keras allows me to quickly prototype and experiment with different neural network architectures.
(162) The researchers studied the cephalon's neural network to understand its decision-making process.
(163) The input-output relationship in this neural network model determines its learning capabilities.
(164) Variational autoencoders are a type of neural network architecture used in unsupervised learning.
(165) The artificial neural network was trained using a supercomputer with a teraflop processing speed.
(166) By applying spectral normalization, the Lipschitz constant of a neural network can be controlled.
(167) The research paper proposed a series-parallel neural network architecture for pattern recognition.
(168) The team conducted intracerebral electrophysiological recordings to study neural network activity.
(169) The topology of a neural network influences its learning capabilities and computational efficiency.
(170) The petaflops achieved by this neural network are enabling breakthroughs in artificial intelligence.
(171) The cephalon's advanced neural network allowed the robot to recognize and respond to human gestures.
(172) The absence of a vector representation for undefined limits its use in neural network architectures.
(173) The convolutional layer in a neural network will convolve the input with a set of learnable filters.
(174) A plane graph can be used to represent the connections between different neurons in a neural network.
(175) The termination condition of the neural network training is when the error rate is below a threshold.
(176) The neural network algorithm was able to detect patterns in the data that were not apparent to humans.
(177) The MNIST dataset is often used to evaluate the performance of different neural network architectures.
(178) The parameter set for this neural network model consists of weights, biases, and activation functions.
(179) Feedforward networks are a type of neural network that can process information in a sequential manner.
(180) The tanh function is a key component of the backpropagation algorithm used in neural network training.
(181) By using a neural network classification method, we were able to classify images based on their content.
(182) The neural network model utilizes a serial-parallel structure to process multiple inputs simultaneously.
(183) The convolutional neural network will convolve the input image with a set of kernels to detect patterns.
(184) The object detection system used a convolutional neural network classifier to identify objects in images.
(185) The microarchitecture of the neural network determines its ability to learn and make accurate predictions.
(186) Spectral normalization can be applied to both convolutional and fully connected layers in a neural network.
(187) The neuroevolutionary paradigm offers a way to overcome the limitations of traditional neural network training.
(188) The feedforward neural network is a type of artificial intelligence that can learn to recognize patterns in data.
(189) Feedforward networks are a type of artificial neural network that can be trained to perform a wide range of tasks.
(190) The convolutional neural network can be used for image classification by convolving the input with a set of filters.
(191) The multiclass classification model was trained using a deep learning architecture called a convolutional neural network.
(192) An example of unsupervised learning is training a neural network to generate realistic images without any labeled examples.
(193) The feedforward neural network is a type of artificial intelligence that can learn to recognize patterns and make predictions.
(194) The grads array is being used to generate a neural network model to predict the future demand for graduates in different industries.
(195) His image recognition software was more accurate because he used convolutional neural network queries to identify objects and features.
(196) Spectral normalization can be seen as a form of regularization that encourages the neural network to have a smooth and well-behaved weight distribution.
(197) Although dendrites are often overlooked in discussions of brain function, they are a crucial component of the neural network that underlies all aspects of cognition and behavior.
Neural Network meaning
Neural Network: A Comprehensive Guide on How to Use this Term in Sentences Introduction: Neural networks have become an integral part of modern technology, revolutionizing various fields such as artificial intelligence, machine learning, and data analysis. Understanding how to use the term "neural network" correctly in sentences is crucial for effective communication in these domains. This article aims to provide you with a comprehensive guide on using the term "neural network" accurately and appropriately. Definition: Before delving into the tips, let's establish a clear definition of a neural network. A neural network is a computational model inspired by the human brain's neural structure. It consists of interconnected nodes, known as artificial neurons or units, which process and transmit information. These networks are designed to recognize patterns, make predictions, and perform complex tasks by learning from large datasets. Tips for Using "Neural Network" in Sentences:
1. Provide a General Explanation: When introducing the term "neural network" in a sentence, it is essential to provide a general explanation to ensure clarity. For example: - "A neural network is a powerful computational model that mimics the human brain's structure and is widely used in machine learning applications."
2. Contextualize the Application: To enhance understanding, it is crucial to provide context by specifying the field or application where neural networks are used. For instance: - "In the field of computer vision, neural networks have significantly improved object recognition accuracy."
3. Explain the Purpose: Elaborating on the purpose of using a neural network in a sentence can help the reader grasp its significance. For example: - "The neural network was employed to predict stock market trends based on historical data."
4. Highlight the Learning Process: One of the key features of neural networks is their ability to learn from data. Emphasizing this aspect can enhance the sentence's impact. For instance: - "By training the neural network on a large dataset of images, it was able to accurately classify objects with high precision."
5. Mention Specific Neural Network Architectures: There are various types of neural network architectures, such as feedforward, recurrent, and convolutional networks. Referring to a specific architecture can add depth to your sentence. For example: - "The convolutional neural network (CNN) is widely used in image recognition tasks due to its ability to capture spatial features."
6. Discuss Performance and Accuracy: When discussing the outcomes of using a neural network, it is essential to mention its performance and accuracy. This provides a quantitative measure of its effectiveness. For instance: - "The neural network achieved an accuracy of 95% in classifying handwritten digits, outperforming traditional algorithms."
7. Compare with Traditional Methods: To highlight the advantages of neural networks, you can compare their performance with traditional methods. For example: - "Compared to traditional regression models, the neural network demonstrated superior predictive capabilities in analyzing customer behavior."
8. Mention Real-World Applications: To showcase the practicality and versatility of neural networks, it is beneficial to mention real-world applications. For instance: - "Neural networks have been successfully applied in autonomous driving systems, enabling vehicles to perceive and respond to their surroundings." Conclusion: Mastering the usage of the term "neural network" in sentences is crucial for effective communication in the fields of artificial intelligence, machine learning, and data analysis. By following the tips provided in this article, you can confidently incorporate this term into your writing, ensuring clarity and precision. Remember to provide explanations, context, and highlight the key features and applications of neural networks to enhance your sentence's impact.
The word usage examples above have been gathered from various sources to reflect current and historical usage of the word Neural Network. They do not represent the opinions of TranslateEN.com.