2,079 results for machine learning
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Machine Learning: de la théorie à la pratique
…élèves ingénieurs. La première édition, connue sous le nom Apprentissage machine, fut traduite en chinois par les éditions iTuring. Dans cette deuxième édi-tion, un nouveau chapitre est dédié au Deep Learning, sur les réseaux de neurones artificiels, et nous avons réorganisé les autres chapitres…
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Découverte du Machine Learning - Les outils de l'apprentissage automatique
International audience
From your institution’s collections
- Machine learning dan computational intelligenceWidodo Budiharto · 2016 · UNILAK
- Machine learning (konsep dan implementasi)Yaya Heryadi · 2020 · UNILAK
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Design sous artifice : la création au risque du machine learning
…ont tendance à se polariser sur le remplacement des humains par la machine. Ce faisant, ils font écran à la question essentielle : quel est le spectre des implications actuelles et potentielles du machine learning pour les pratiques de design ?
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Stellar Classification by Machine Learning
As an emerging subject with strong comprehensiveness, machine learning has made varying degrees of progress in various fields. In the field of astronomy, it has also been generally used, and there have been quantities of research using machine learning for data processing and model prediction. The…
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Journal Article
Quantum Chemistry Meets Machine Learning
In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the power brought by kernel-based approaches in…
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Machine learning methods in finance
This article focuses on supervised learning and reinforcement learning. These areas overlap most with econometrics, predictive modelling, and optimal control in finance. We choose to focus on how to cast machine learning into various financial modelling and decision frameworks. This work introduces…
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Machine learning for algorithmic trading
The purpose of the study is to confirm the feasibility of using machine learning methods to predict the behavior of the foreign exchange market. The article examines the theoretical and practical aspects of the implementation of artificial neural networks in the process of Internet trading. We…
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Journal Article
Machine Learning, Understanding, and Interaction
High-performance machine learning models generally suffer from a lack of transparency that calls into question the ability of humans to understand how they work. Through the study of CoMo, an interactive learning system that allows users to associate sounds and gestures, we show that a form of…
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Machine Learning at the Atomic Scale
Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of molecules and condensed-phase systems. This short review…
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Machine Learning Frameworks in Cancer Detection
…from the bioscience and genomics field to investigate the utilization of machine learning (ML) algorithms in cancer diagnosis and treatment. Because of this, these methods have been used with the goal of simulating the development and treatment of malignant diseases in humans. Furthermore, the…
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Optimizing truss members using Machine Learning
This paper aims to produce an optimization methodology for a truss for minimal stress on critical sections using Machine learning models. This is done by varying the height and length of the truss span and applying live loads on different joints. The optimization of the truss is done through feed…
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Electricity Consumption Prediction Using Machine Learning
…anticipate power use using previous data thanks to improvements in machine learning techniques. In this paper, we provide a machine learning-based method for forecasting power use. In this study, we investigate a number of machine learning techniques, including linear regression, K Nearest…
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Improving Enzyme Fitness with Machine Learning
The combinatorial composition of proteins has triggered the application of machine learning in enzyme engineering. By predicting how protein sequence encodes function, researchers aim to leverage machine learning models to select a reduced number of optimized sequences for laboratory measurement…
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Exploring Chemical Space with Machine Learning
…in the area of drug discovery. Here we review our implementations of machine learning in this project, including our use of deep neural networks to enumerate the GDB13 database from a small sample set, to generate analogs of drugs and natural products after training with fragment-size molecules…
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Machine learning for filter pollution control
…Subsequent considerations focuses on the test-rig measurements. The machine learning algorithm was trained successfully to detect anomalies of the filter behavior. Finally, the change intervals of the filter may be adapted to the real degree of pollution without the requirement for visual…
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Machine Learning in Stock Price Forecast
This paper analyzed and compared the forecast effect of three machine learning algorithms (multiple linear regression, random forest and LSTM network) in stock price forecast using the closing price data of NASDAQ ETF and data of statistical factors. The test results show that the prediction effect…
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Empowering Software Development with Machine Learning
Machine learning (ML) has emerged as a transformative technology across various domains, including software development. This paper delves into the significant roles ML plays in enhancing and optimizing the software development lifecycle (SDLC). By integrating ML into different phases of software…
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Adaptive dermascopy application using machine learning
Skin cancer is the most lethal because skin cells develop abnormally. Finding skin cancer early is very important and may help stop some kinds of skin cancer, like melanoma and focal cell carcinoma. Early detection and classification of skin cancer are difficult and costly. Recurrent networks and…
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Thyroid Disease Classification using Machine Learning Algorithms
…based on the information gathered from the dataset taken from the UCI machine learning repository. Machine learning plays a crucial role in the detection of thyroid disease. This paper suggests various machine-learning methods for thyroid detection and diagnosis for thyroid prevention.
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