3.327 hasil untuk machine learning
Menampilkan 281–300 · 1,58 detik · RSS
-
Artikel Jurnal Teks lengkap
Challenges in Deploying Machine Learning: A Survey of Case Studies
In recent years, machine learning has transitioned from a field of academic research interest to a field capable of solving real-world business problems. However, the deployment of machine learning models in production systems can present a number of issues and concerns. This survey reviews…
-
Artikel Jurnal Teks lengkap
Significance of machine learning in healthcare: Features, pillars and applications
Machine Learning (ML) applications are making a considerable impact on healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the speed and accuracy of physicians' work. Countries are currently dealing with an overburdened healthcare system with a shortage of…
-
Artikel Jurnal Teks lengkap
Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions
-
Artikel Jurnal Teks lengkap
Integration strategies of multi-omics data for machine learning analysis
…and metabolomics. New insight from these data have been obtained by machine learning algorithms that have produced diagnostic and classification biomarkers. Most biomarkers obtained to date however only include one omic measurement at a time and thus do not take full advantage of recent multi-omics…
-
Artikel Jurnal Teks lengkap
On hyperparameter optimization of machine learning algorithms: Theory and practice
-
Artikel Jurnal Teks lengkap
Improving the accuracy of medical diagnosis with causal machine learning
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis are purely associative, identifying diseases…
-
Artikel Jurnal Teks lengkap
Edge Machine Learning for AI-Enabled IoT Devices: A Review
…surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors' data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network…
-
Artikel Jurnal
Predictably Unequal? The Effects of Machine Learning on Credit Markets
…Using data on U.S. mortgages, we predict default using traditional and machine learning models. We find that Black and Hispanic borrowers are disproportionately less likely to gain from the introduction of machine learning. In a simple equilibrium credit market model, machine learning increases…
-
Artikel Jurnal
Recent Advances in Machine Learning for Fiber Optic Sensor Applications
…advanced data analytics engines enabled by recent breakthroughs in machine learning (ML) and artificial intelligence (AI). This article presents a comprehensive review of recent studies that integrate ML and AI algorithms with FOS technologies. This review also highlights several FOS technology…
-
Artikel Jurnal Teks lengkap
Crop Yield Prediction through Proximal Sensing and Machine Learning Algorithms
…in combination with innovative methods of data processing such as machine learning (ML) algorithms for the extraction of useful information responsible for controlling crop yield. Four ML algorithms, namely linear regression (LR), elastic net (EN), k-nearest neighbor (k-NN), and support vector…
-
Artikel Jurnal Teks lengkap
Machine learning on small size samples: A synthetic knowledge synthesis
Machine Learning is an increasingly important technology dealing with the growing complexity of the digitalised world. Despite the fact, that we live in a 'Big data' world where, almost 'everything' is digitally stored, there are many real-world situations, where researchers are still faced with…
-
Artikel Jurnal
Modelling Supply Chain Information Collaboration Empowered with Machine Learning Technique
…prefer to partner with reputable and viable firms. In this respect, machine learning methodology such as Support Vector Machine is used to jeopardize the supply chain information collaboration. More specific efficiency is obtained from the more productive device model. Simulation results show that…
-
Artikel Jurnal
Robust machine learning algorithms for predicting coastal water quality index
…The aim of the research is to determine the most reliable and robust machine learning (ML) algorithm(s) to anticipate WQIs at each monitoring point instead of repeatedly employing SI and weight values in order to reduce model uncertainty. In this study, we compared eight commonly used algorithms…
-
Artikel Jurnal Teks lengkap
Phishing Detection System Through Hybrid Machine Learning Based on URL
…no complete and proper solution for frustrating them. Therefore, machine learning plays a vital role in defending against cybercrimes involving phishing attacks. The proposed study is based on the phishing URL-based dataset extracted from the famous dataset repository, which consists of phishing…
-
Artikel Jurnal Teks lengkap
A Review of Physics-Informed Machine Learning in Fluid Mechanics
Physics-informed machine-learning (PIML) enables the integration of domain knowledge with machine learning (ML) algorithms, which results in higher data efficiency and more stable predictions. This provides opportunities for augmenting—and even replacing—high-fidelity numerical simulations of…
-
Artikel Jurnal Teks lengkap
Data drift in medical machine learning: implications and potential remedies
Data drift refers to differences between the data used in training a machine learning (ML) model and that applied to the model in real-world operation. Medical ML systems can be exposed to various forms of data drift, including differences between the data sampled for training and used in clinical…
-
Artikel Jurnal Teks lengkap
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
Data science, and machine learning in particular, is rapidly transforming the scientific and industrial landscapes. The aerospace industry is poised to capitalize on big data and machine learning, which excels at solving the types of multi-objective, constrained optimization problems that arise in…
-
Artikel Jurnal Teks lengkap
Prediction of Type 2 Diabetes Based on Machine Learning Algorithm
…or delay the progression of the disease. In this study, we developed a machine learning (ML) model to predict T2D occurrence in the following year (Y + 1) using variables in the current year (Y). The dataset for this study was collected at a private medical institute as electronic health records…
-
Artikel Jurnal
Flood forecasting with machine learning models in an operational framework
…stage forecasting, inundation modeling, and alert distribution. Machine learning is used for two of the subsystems. Stage forecasting is modeled with the long short-term memory (LSTM) networks and the linear models. Flood inundation is computed with the thresholding and the manifold models, where…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.