Results 151 to 160 of about 1,710,361 (207)
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A review paper on Machine Learning (ML)
Smart Computing, 2021A. Sharma, Neha Goel
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Global Power, Energy and Communication Conference, 2023
The use of artificial intelligence (AI) and machine learning (ML) in electric vehicles (EVs) is gaining popularity as a means of improving information security.
Nachaat Mohamed +5 more
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The use of artificial intelligence (AI) and machine learning (ML) in electric vehicles (EVs) is gaining popularity as a means of improving information security.
Nachaat Mohamed +5 more
semanticscholar +1 more source
Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
Reviews in the Neurosciences, 2020Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long diagnostic period encountered in the early years of life. If diagnosed early, the negative effects of this disease can be reduced by starting special education early ...
H. Nogay, H. Adeli
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Leaf Disease Detection Using Machine Learning (ML)
2023This method's central idea is the generation of features using grey level co-occurrence matrices (GLCM). The spatial interactions between pixels are to be measured by the matrices. A grey-level co-occurrence matrix is used to extract co-occurrence features. Texture classification can be used for a number of applications, such as pattern identification,
C.V. Suresh Babu +4 more
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2020
This chapter introduces the Core ML API and shows how it is now possible to use contemporary machine learning models to implement intelligent image analysis and computer vision solutions, such as object detection and recognition and scene classification.
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This chapter introduces the Core ML API and shows how it is now possible to use contemporary machine learning models to implement intelligent image analysis and computer vision solutions, such as object detection and recognition and scene classification.
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ML Deployment Pipeline Using Oracle Machine Learning
2021As large-scale model-driven applications are being deployed at an ever-increasing pace, enterprises and industries are racing to adopt technology that makes the process of building and maintaining these applications more efficient and less expensive. A machine learning (ML) platform is the data center software and hardware infrastructure that automates
Heli Helskyaho, Jean Yu, Kai Yu
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ML Suite: An Auto Machine Learning Tool
2020In today’s age, it is important for some businesses to upgrade to machine learning techniques. The aim of this project is to create an autonomous platform for researchers/laymen who operate on data, which would auto-clean the data and suggest machine learning approach to understand and get better value out of data.
Nilesh M. Patil +2 more
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Implementation of Machine Learning (ML) in Biomedical Engineering
Transaction on Biomedical Engineering Applications and Healthcare, 2021The subfields within AI have been discussed throughout the article and the findings of the article have provided a positive outcome. ML has a huge potential through ML methodologies such as supervised and unsupervised learning as discussed in the article.
Prof. Kshatrapal Singh +1 more
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Heart Disease Prediction Using Machine Learning Algorithms
International Conference on Smart Communications and NetworkingHeart disease is a prevalent and complex condition that affects numerous individuals worldwide. Timely and accurate diagnosis of heart disease is of utmost importance in cardiology. In this research article, we propose an efficient and precise system for
Dina Jrab +3 more
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MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
arXiv.orgWe introduce MLE-bench, a benchmark for measuring how well AI agents perform at machine learning engineering. To this end, we curate 75 ML engineering-related competitions from Kaggle, creating a diverse set of challenging tasks that test real-world ML ...
Jun Shern Chan +11 more
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