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...

Celý popis

Uloženo v:

Podrobná bibliografie
Médium:	E-kniha
Jazyk:	angličtina
Vydáno:	Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Témata:	academic performance adaptive camouflage adaptive e-learning systems advanced design methods airflow signal answer set programming anticipatory classifier systems ARIMA artificial neural network autoencoder autoencoders backpropagation neural network backscatter data BERT big data BiLSTM Bitcoin cascaded classifier Chenab River Basin classification climate change impact climate zone cloud detection code auto-completion comparison of various techniques for topic classification compressive strength Computer science computer vision Computing and Information Technology construction productivity construction safety construction site management consumer classification context-aware convolutional neural network convolutional neural network (CNN) convolutional neural networks COREG algorithm cost-benefit function course grades COVID cross referencing topic crossover crowdfunding cyber security cyclical learning rate data mining decision tree deep learning deep multi-target prediction deep neural network deep neural networks drifter trajectory early prognosis earning rate Economics, Finance, Business and Management educational data mining evolutionary computation extreme gradient boosting feature analysis Felder–Silverman learning style fly ash Gaussian Mixture Models (GMM) genetic algorithms genetic programming geopolymer concrete GPT-2 model grade point average grammatical inference GRNN healthcare heatwaves higher order neural network human resources hybrid models image completion image representation Industry and industrial studies Information technology industries instance selection interpretation investigation framework Jhelum River Basin k-means KdV equation KdV-Burgers equation keyword extraction large-scale dataset LDA learning classifier systems lidar ceilometer live prediction local features LSTM machine learning machine learning algorithms Machine learning analysis management mass operator Media, entertainment, information and communication industries micro-blogs (Twitter) multiple linear regression n/a nature language processing NCLS neural network NLP non-deterministic automata induction object detection online taxi-hailing demand OpenAI gym optimization over-the-top parsing expression grammar partial differential equations performance measurement personal teaching and learning physics-informed neural network prediction predictive analytics preprocessing Principal Component Analysis project recommendation system Prophet random forest regression model real-time prediction reinforcement learning relative support distance remote sensing ResNet robust matrix factorization rumor refuter sales saliency detection sampling scene classification semi-regression sentence modeling sentiment analysis side information graph sleep apnea social media social network services stock performance structural stress student grade prediction student performance prediction superpixel segmentation support vector candidates support vector machine support vector machines SVM synthetic data text representation time-aware classification time-series predictions topic analysis towards recommending influencers based on topic classification tracking transfer learning TripAdvisor undergraduate user generated content vibration test volatility volatility forecasting vulnerability detection warehouse optimization wave equation weather detection weather nowcasting word embedding XGBoost
ISBN:	9783036579061, 3036579060, 3036579079, 9783036579078
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!