Applied Machine Learning

This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, machine learning models; undertakes cr...

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Bibliografiske detaljer
Format:	Online
Sprog:	engelsk
Udgivet:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Fag:	robust matrix factorization student grade prediction educational data mining side information graph personal teaching and learning deep multi-target prediction Felder–Silverman learning style adaptive e-learning systems artificial neural network deep learning transfer learning student performance prediction Machine learning analysis sentence modeling topic analysis cross referencing topic machine learning classification preprocessing instance selection data mining predictive analytics sales performance measurement human resources rumor refuter nature language processing XGBoost feature analysis Bitcoin higher order neural network volatility forecasting hybrid models warehouse optimization genetic algorithms crossover construction productivity construction safety synthetic data tracking academic performance course grades grade point average prediction undergraduate cloud detection superpixel segmentation convolutional neural networks support vector machines machine learning algorithms multiple linear regression SVM management social network services image representation local features autoencoder convolutional neural network user generated content sentiment analysis keyword extraction text representation sampling TripAdvisor adaptive camouflage convolutional neural network (CNN) k-means object detection image completion saliency detection social media micro-blogs (Twitter) towards recommending influencers based on topic classification investigation framework comparison of various techniques for topic classification cost-benefit function partial differential equations physics-informed neural network wave equation KdV-Burgers equation KdV equation neural network cyclical learning rate remote sensing scene classification backscatter data lidar ceilometer weather detection online taxi-hailing demand backpropagation neural network extreme gradient boosting real-time prediction climate zone climate change impact Jhelum River Basin Chenab River Basin support vector machine decision tree large-scale dataset relative support distance support vector candidates answer set programming non-deterministic automata induction grammatical inference geopolymer concrete deep neural network ResNet compressive strength fly ash sleep apnea airflow signal Gaussian Mixture Models (GMM) cyber security vulnerability detection word embedding drifter trajectory evolutionary computation NCLS stock performance earning rate volatility heatwaves big data random forest regression model semi-regression early prognosis interpretation COREG algorithm cascaded classifier computer vision construction site management consumer classification over-the-top time-aware classification code auto-completion GPT-2 model advanced design methods mass operator structural stress live prediction vibration test genetic programming parsing expression grammar BiLSTM BERT NLP context-aware LDA LSTM crowdfunding project recommendation system optimization weather nowcasting deep neural networks autoencoders Principal Component Analysis learning classifier systems anticipatory classifier systems reinforcement learning OpenAI gym healthcare COVID time-series predictions ARIMA Prophet GRNN n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science
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Summary:	This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, machine learning models; undertakes critical comparisons with existing techniques; and presents an interpretation of the results. The topics within the chapters of the publication fall into six categories: computer vision, teaching and learning, social media, forecasting, basic problems of machine learning, and other topics.

Applied Machine Learning

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