關於 deep learning models ，我們在網路上蒐集到這些相關的討論、資訊與評價

#11. What is a machine learning model? | Microsoft Docs

A machine learning model is a file that has been trained to recognize certain types of patterns. You train a model over a set of data, ...

#12. What Is a Machine Learning Model? | NVIDIA Blogs

A machine learning model is an expression of an algorithm that combs through mountains of data to find patterns or make predictions.

#13. List of Deep Learning Models - Preprints.org

There has been an enormous evolution in system modeling and intelligence af- ter introducing the early models for deep learning [1-8]. Deep ...

#14. List of Deep Learning Models | SpringerLink

2 Deep Learning Methods ... Convolutional neural network (CNN) Recurrent neural network (RNN), Denoising autoencoder (DAE), deep belief networks ( ...

#15. AI vs. Machine Learning vs. Deep Learning vs. Neural Networks

With that said, a deep learning model would require more data points to improve its accuracy, whereas a machine learning model relies on less ...

#16. (PDF) List of Deep Learning Models - ResearchGate

Deep learning (DL) algorithms have recently emerged from machine learning and soft computing techniques. Since then, several deep learning (DL) ...

#17. Keras: the Python deep learning API

It's not only possible; it's easy. Deploy anywhere. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models ...

#18. Deep Learning on AWS

Using cloud computing for deep learning allows large datasets to be easily ingested and managed to train algorithms, and it allows deep learning models to scale ...

#19. Best Practices for Improving Your Machine Learning and ...

To improve your machine learning or deep learning model, it's important to establish a strong baseline model.

#20. [2103.10689] Interpretable Deep Learning - arXiv

... handling various machine learning and artificial intelligence tasks. ... difficult to understand the prediction results of deep models.

#21. Building Deep Learning Models with TensorFlow | Coursera

Shallow neural networks cannot easily capture relevant structure in, for instance, images, sound, and textual data. Deep networks are capable of discovering ...

#22. Compression of Deep Learning Models for Resource ...

To compress deep learning models, two approaches exist: compression during training and compression of the trained model. Moreover, various techniques are ...

#23. Improving performance of deep learning models with ... - Nature

Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; ...

#24. Models - Machine Learning - Apple Developer

Build intelligence into your apps using machine learning models from the research community designed for Core ML.

#25. Demystifying deep learning - TechTalks

This is how deep learning models classify images, transform voice to text, predict stock prices, and perform many other complicated tasks. deep ...

#26. The Description Length of Deep Learning models - NeurIPS ...

Authors. Léonard Blier, Yann Ollivier. Abstract. Deep learning models often have more parameters than observations, and still perform well.

#27. Deep Learning Models of the Retinal Response to Natural ...

A central challenge in sensory neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant ...

#28. Teachable Machine

Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more – no ...

#29. Deep learning vs. machine learning – What's the difference?

Machine learning means computers learning from data using algorithms to perform a task without being explicitly programmed. Deep learning uses a ...

#30. Build Deep Learning Models with TensorFlow | Codecademy

Deep learning is a cutting-edge form of machine learning inspired by the architecture of the human brain, but it doesn't have to be intimidating. With ...

#31. Interpretability of deep learning models: A survey of results

Abstract: Deep neural networks have achieved near-human accuracy levels in various types of classification and prediction tasks including images, text, ...

#32. Deep Neural Network: The 3 Popular Types (MLP, CNN and ...

Deep neural network models were originally inspired by neurobiology. On a high level, a biological neuron receives multiple signals through the ...

#33. Deep Learning for Computer Vision - Run:AI

Computer vision models are designed to translate visual data based on features and contextual information identified during training. This enables models to ...

#34. Deploying Deep Learning Models to NI Hardware

Deploy a Deep Learning Model with LabVIEW ... The Vision Development Module in LabVIEW works with frozen deep learning models developed using ...

#35. Deep Learning Models for Medical Imaging - 1st Edition

Purchase Deep Learning Models for Medical Imaging - 1st Edition. Print Book & E-Book. ISBN 9780128235041, 9780128236505.

#36. Deep Learning Models and Tools - SAS Support

Deep Learning Models, Examples, and Utilities. ... ResNet101: Network file, model parameter file, and layer mapping file for the convolutional neural ...

#37. The Description Length of Deep Learning models - NeurIPS ...

deep learning models are significantly simpler than their numbers of parameters might suggest. In information theory and Minimum Description Length (MDL), ...

#38. Ensemble Deep Learning Models - Analytics Vidhya

Ensembling is the process of combining multiple learning algorithms to obtain their collective performance i.e., to improve the performance of ...

#39. Interpretability Methods in Machine Learning: A Brief Survey

Some machine learning models are interpretable by themselves. For example, for a linear model, the predicted outcome Y is a weighted sum of its features X. You ...

#40. Introduction to Deep Learning Models - OpenClassrooms

This course is a practical introduction to neural networks. ^^. Part 1 will explore the differences between machine learning and deep learning, ...

#41. Train Deep Learning Models - L3Harris Geospatial

Training a deep learning model involves a number of stochastic processes that contain a certain degree of randomness. Training with the same parameters will ...

#42. Pretrained deep learning models update (July 2021) - Esri

Esri has released many new pretrained deep learning models for feature extraction workflows. Here's an overview of what to expect.

#43. DeepCPU: Serving RNN-based Deep Learning Models 10x ...

Abstract: Recurrent neural networks (RNNs) are an important class of deep learning (DL) models. Existing DL frameworks have unsatisfying performance for online ...

#44. Why you need to explain machine learning models - Google ...

Explainable AI (XAI) is a set of tools and frameworks that can be used to help you understand how your machine learning models make decisions.

#45. A New Link to an Old Model Could Crack the Mystery of Deep ...

In the usual way of thinking, machine learning models — including neural networks, trained to learn about patterns in sample data in order to ...

#46. Machine Learning Engineering for Production (MLOps)

Design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment requirements. · Establish a model baseline, address ...

#47. 7 Awesome Types of Deep Learning Networks - eduCBA

Types of Deep Learning Networks · 1. Feedforward neural network · 2. Radial basis function neural networks · 3. Multi-layer perceptron · 4. Convolution neural ...

#48. Machine Learning Models Explained - AI Wiki - Gradient Docs

A model is a distilled representation of what a machine learning system has learned. Machine learning models are akin to mathematical functions -- they take ...

#49. Top 8 Deep Learning Frameworks - Maruti Techlabs

Popularly known for easy training and a combination of popular model types across servers, the Microsoft Cognitive Toolkit (earlier known as CNTK) is an open- ...

#50. scikit-learn: machine learning in Python — scikit-learn 1.0.1 ...

Comparing, validating and choosing parameters and models. ... Applications: Transforming input data such as text for use with machine learning algorithms.

#51. Deep Learning Online Course - Udacity

Learn to build and apply your own deep neural networks to challenges like image classification, prediction, and model deployment. Learn online with Udacity.

#52. deepImageJ • Home

The plugin bridges the gap between developers of deep-learning models and end-users in life-science applications. It favors the sharing of trained models ...

#53. CloudLeak: Large-Scale Deep Learning Models Stealing ...

CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples ... Cloud-based Machine Learning as a Service (MLaaS) is gradually gaining ...

#54. Top 8 Machine Learning Models | Analytics Steps

A machine learning model is a computer software that has been taught to recognise particular patterns. You train a model on a set of data ...

#55. 5 Steps for Building Machine Learning Models for Business

5 Steps for Building Machine Learning Models for Business · 1. Ask Yourself If It's the Right Time for Machine Learning? · 2. Keep It Simple · 3.

#56. 10 Real World Examples of Deep Learning Models & AI

10 Real World Examples of Deep Learning Models & AI · 1. Computer vision. Computer Vision · 2. Sentiment based news aggregation · 3. Bots based on ...

#57. Machine Learning Glossary | Google Developers

A probabilistic neural network that accounts for uncertainty in weights and outputs. A standard neural network regression model typically ...

#58. Facebook Open-Sources GHN-2 AI for Fast Initialization of ...

Our meta-model can predict parameters for almost any neural network in just one forward pass. Training a deep-learning model on a dataset is ...

#59. A foolproof way to shrink deep learning models | MIT News

MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results ...

#60. Deep Learning — Dataiku DSS 10.0 documentation

Introduction · Your first deep learning model · Create a code environment with the required packages · Model architecture · Build Keras model · Training · Multiple ...

#61. How to Train Large Deep Learning Models as a Startup

Training large deep learning models is expensive and slow. Yet, startups are all about iterating fast. In this post, we share the lessons ...

#62. Your First Machine Learning Model | Kaggle

Many machine learning models allow some randomness in model training. Specifying a number for random_state ensures you get the same results in each run.

#63. The Five Ways To Build Machine Learning Models - Forbes

A machine learning model is the product of training a machine learning algorithm with training data. In other words, it is the result of a ...

#64. Wide & Deep Learning: Better Together with TensorFlow

It's not an easy question to answer, but by jointly training a wide linear model (for memorization) alongside a deep neural network (for ...

#65. Artificial Intelligence vs. Machine Learning vs. Deep Learning

Schematic representation of a neural network. Artificial neural networks have unique capabilities that enable deep learning models to solve ...

#66. Deep Learning vs. Machine Learning: What's the difference?

How does deep learning work? · Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it ...

#67. Evaluating Deep Learning models for predicting ALK-5 inhibition

The generalization power of the models was assessed by internal and external validation procedures. A deep neural network model obtained the ...

#68. Deep Learning | Dynamic Optimization - APMonitor

A trained model predicts outcomes based on new input conditions that aren't in the original data set. Some of the typical steps for building and deploying a ...

#69. Deep Learning vs. Machine Learning — What's the Difference?

Deep learning models introduce an extremely sophisticated approach to machine learning and are set to tackle these challenges because ...

#70. Machine Learning, Deep Learning, and AI - Datanami

In plain English, a deep learning model will learn the features that are important by itself, instead of requiring the data scientist to ...

#71. The Difference Between Deep Learning Training and Inference

Deep learning inference is the process of using a trained DNN model to make predictions against previously unseen data. As explained above, the DL training ...

#72. Improve Deep Learning Models performance & deep network ...

Improve Deep Learning Models performance & deep network tuning (Part 6) · Analyze errors (bad predictions) in the validation dataset. · Monitor the activations.

#73. Development of Deep Learning Models for Predicting the ...

Machine learning has been used extensively in nanoinformatics to develop predictive models for toxicity- and ecotoxicity-related endpoints, ...

#74. New deep learning model to speed up ecological surveys

Scientists have developed a new deep-learning model to count the number of seals in aerial photos that is considerably faster.

#75. Recycling Deep Learning Models with Transfer Learning

Deep learning exploits gigantic datasets to produce powerful models. But what can we do when our datasets are comparatively small? Transfer learning by ...

#76. 機器學習自學筆記07: Deep Learning

結果是可想而知的，因為本來model的parameter越多，它cover的function set就越多，它的bias就越小，如果今天你有足夠多的training data去控制它的variance ...

#77. Explainable Artificial Intelligence (xAI) Approaches and Deep ...

While a classic deep learning model can answer “what” or “who” questions, learning models in explainable artificial intelligence approaches can ...

#78. Deep Learning Algorithms - The Complete Guide | AI Summer

BERT and GPT-2 are considered the two best language models and they are in fact Transformer based Sequence models . Deep Learning in Computer ...

#79. New deep learning models: Fewer neurons, more intelligence

Mar. 19, 2020 — Scientists have demonstrated fully-autonomous SPM operation, applying artificial intelligence and deep learning to remove the ...

#80. Compression of Deep Learning Models for NLP - ACM Digital ...

In recent years, the fields of NLP and information retrieval have made tremendous progress thanks to deep learning models like RNNs and ...

#81. Keras Tutorial: Deep Learning in Python - DataCamp

One of the most powerful and easy-to-use Python libraries for developing and evaluating deep learning models is Keras; It wraps the efficient numerical ...

#82. Explainable Deep Learning Models in Medical Image Analysis

Deep learning methods have been very effective for a variety of medical diagnostic tasks and have even outperformed human experts on some of those.

#83. Top Machine Learning Frameworks To Use in 2021 - BMC ...

TensorFlow is among the de facto machine learning frameworks used today, and it is free. (Google thinks the library can be free, but ML models ...

#84. The unreasonable effectiveness of deep learning in artificial ...

There is a stark contrast between the complexity of real neurons and the simplicity of the model neurons in neural network models. Neurons are ...

#85. Development and Validation of a Deep Learning Model for ...

This diagnostic study assesses the ability of a deep learning model to detect evidence of cognitive decline before a diagnosis of mild ...

#86. Comparative study of deep learning models for optical ...

Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Meanwhile, deep learning has ...

#87. Want to know how Deep Learning works? Here's a quick ...

Deep Learning is a machine learning method. It allows us to train an AI to predict outputs, given a set of inputs. Both supervised and ...

#88. Different Types Of Deep Learning Models Explained

Deep learning is a class of machine learning techniques that exploit many layers of non-linear information processing for supervised or ...

#89. What Is Deep Learning and Why Is It More Relevant Than Ever?

Deep learning computer models learn to perform classification tasks directly from images, text, or even sound. A deep learning model can “ learn ...

#90. AWS introduces new Trn1 chips to speed up training of ...

... Trainium chip, designed specifically for machine learning models. ... for training deep learning models in the cloud and the fastest on ...

#91. Building deep learning models for evidence classification from ...

Abstract. We investigate the application of deep learning to biocuration tasks that involve classification of text associated with ...

#92. How to version control your production machine learning models

Machine learning (ML) is about rapid experimentation and iteration, and without keeping track of your modeling history you won't be able to ...

#93. Dispelling Myths: Deep Learning vs. Machine Learning - Merkle

They both start with splitting input data into training and testing, fitting a model, and going through an optimization process to find the ...

#94. Comparison of the Performance of Machine Learning Models ...

Free energy surfaces of chemical and physical systems are often generated using a popular class of enhanced sampling methods that target a ...

#95. Machine Learning: Models And Algorithms - SSRN

This textbook introduces the mathematical models and algorithms utilised in machine learning, covering supervised and unsupervised learning ...