Arama Sonuçları - machine learning ((mathematical model) OR (mathematical models)).

Optimization for machine learning /

Konular: “…Machine learning Mathematical models. 46147…”

Makine öğrenmesi / Yazar: Gürsakal, Necmi

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Analysis and Mathematical Models of Canned Electrical Machine Drives In Particular a Canned Switched Reluctance Machine / Yazar: Yu, Qiang, Wang, Xuesong, Cheng, Yuhu, Tian, Lisi

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Machine Learning for Model Order Reduction Yazar: Mohamed, Khaled Salah

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Applied Physics, System Science and Computers II Proceedings of the 2nd International Conference on Applied Physics, System Science and Computers (APSAC2017), September 27-29, 2017...

İçindekiler: “…Noticing of Volume Fraction Limiting -- Simulation of the Inflow to a Well Equipped with a Vertical Slot Filter -- Errors of Approximation with Polynomial Splines of the Fifth Order -- Classical Potential Barrier of Liquid Phase Radical Reactions and Its Simulation Based on the Experimental Kinetic and Thermochemical Data Using Fuzzy Neural Networks -- Type of Substance as a New Physical Quantity -- Spectroscopy of Colorants for Fine Art in Visual and Near Infrared Spectrum -- From Quantum Sensing to SWEME Interaction Modeling -- An Ultrasound Technique for the Characterization of the Acoustic Emission of Reinforced Concrete Beam -- Prediction of Airport Acoustical Noise by Deterministic Decomposition and Seasonal ARIMA Techniques -- Express Registration of Partial Discharges in Gas-insulated Switchgear -- Risk Factors for the Occurrence of Traumatic Vacuum Phenomenon After Chest Compression for Patients with Cardiac Arrest -- A System for Big Attributed Hierarchical Graph Visualization -- A System of Functional Programming for Supporting Cloud Supercomputing -- Security and Performance of a Textual Substitution Compression Method Applied to Images -- A Solution of the Mastermind Board Game in Scratch Suitable for Algorithmic Thinking Development -- The Development of KarelNXT Robot as a Simulation of xKarel Programming Language -- Development of Polytechnic Creativity of Primary School Pupils -- Distribution and Validation of Meteorological Data for the Air Traffic Management Systems -- HLA Simulation of Customer Flow in a Polyclinic -- Steganographic Principle for Transfer Hidden Pictures within Pictures -- Assets as Part of Tertiary Technical Education -- Using of the Tablets for Amplyopia Treatment -- Neural Interface: The potential of Using Cheap EEG Devices for Scientific Purposes -- Optimal Information Paths in Social Media: Personalized Consumption of Tweets -- Solving Sparse Matrices: a Comparative Analysis between FPGA and GPU -- Making a Shift from Believing to Knowing by the Help of RDF CFL Formal Representation -- Deformation Analysis in Image Sequences by Physics-Inspired Virtual Current Interaction -- Utilization of NFV in Cloud Data Center -- Autonomic Machine Learning for Intelligent Databases -- Recommender System for Post-editing of Machine Translation -- Neural Network methods for Image Segmentation -- An HPC-Data Center Case Study on the Power Consumption of Workload -- Identifying Problematic e-Courses Content Based on Students Behaviour -- Dyscalculia: A Behavioural Vision -- Enhancing the Development of Interaction between Authorities in Maritime Surveillance -- Electricity Peak Demand Classification with Machine Learning Techniques -- Theϵ-Complexity of Finite-Dimensional Continuous Maps -- Characterisation of the Vibration of an Ultrasonic Transducer for Guided Waves Applications -- Asymptotic Stability of Partial Difference Equations Systems with Singular Matrix -- Chaos and Stability of the Financial System -- A Simple Econophysics Model of the Stock Market as a Nonequilibrium Open System -- Mathematical Modeling and Simulation of Selected Multipulse Rectifiers, Used in "Conventional" Airplanes and Aircrafts Consistent with the Trend of "MEA/AEA" -- A Sufficient Asymptotic Stability Condition in Generalised Model Predictive Control to Avoid Input Saturation -- Minimization of Dynamic Loads in the Reciprocating Motion of the Executive Links of a Large Mass -- Harmonic Analysis in a Node Where Exist a Deformed Regime -- Human Upper Limb Motions Video Analysis Used for Rehabilitation Robotics -- Interactive Control System Proposal for High Switching Frequency Resonant Converters -- PWM Controlled Single-Phase Induction Motor Supplied from Single-Leg MxC -- Forward and Inverse Kinematics Using Transposition Method for Robotic Arm DOBOT -- Integral Assessment of Power Network Equipment Operational Risks: Special Aspects.…”
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Intelligent Random Walk: An Approach Based on Learning Automata Yazar: Saghiri, Ali Mohammad, Khomami, M. Daliri, Meybodi, Mohammad Reza

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Social Network Forensics, Cyber Security, and Machine Learning Yazar: Krishna, P. Venkata, Gurumoorthy, Sasikumar, Obaidat, Mohammad S.

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Electromagnetic Linear Machines with Dual Halbach Array Design and Analysis / Yazar: Yan, Liang, Zhang, Lu, Peng, Juanjuan, Zhang, Lei, Jiao, Zongxia

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Python for Probability, Statistics, and Machine Learning Yazar: Unpingco, José

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Fuzzy hybrid computing in construction engineering and management : theory and applications /

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Problems & Solutions in Inventory Management Yazar: Shenoy, Dinesh, Rosas, Roberto

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Computational Intelligence, Cyber Security and Computational Models Proceedings of ICC3 2015 /

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Handbook of Deep Learning Applications

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Twin Support Vector Machines Models, Extensions and Applications / Yazar: Jayadeva, Khemchandani, Reshma, Chandra, Suresh

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An Introduction to Machine Learning Yazar: Rebala, Gopinath, Ravi, Ajay, Churiwala, Sanjay

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Deep Learning : Foundations and Concepts. Yazar: Bishop, Christopher M.

İçindekiler: “…Bayesian Probabilities -- 2.6.1 Model parameters -- 2.6.2 Regularization -- 2.6.3 Bayesian machine learning -- Exercises -- 3 Standard Distributions -- 3.1. …”
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Advances in Hybridization of Intelligent Methods Models, Systems and Applications /

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Deep Learning with Python, Second Edition. Yazar: Chollet, Francois

İçindekiler: “…-- 1.1 Artificial intelligence, machine learning, and deep learning -- 1.1.1 Artificial intelligence -- 1.1.2 Machine learning -- 1.1.3 Learning rules and representations from data -- 1.1.4 The "deep" in "deep learning" -- 1.1.5 Understanding how deep learning works, in three figures -- 1.1.6 What deep learning has achieved so far -- 1.1.7 Don't believe the short-term hype -- 1.1.8 The promise of AI -- 1.2 Before deep learning: A brief history of machine learning -- 1.2.1 Probabilistic modeling -- 1.2.2 Early neural networks -- 1.2.3 Kernel methods -- 1.2.4 Decision trees, random forests, and gradient boosting machines -- 1.2.5 Back to neural networks -- 1.2.6 What makes deep learning different -- 1.2.7 The modern machine learning landscape -- 1.3 Why deep learning? …”
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Deep Learning with TensorFlow and Keras - 3rd Edition : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models. Yazar: Kapoor, Amita

İçindekiler: “…Multiple and multivariate linear regression using the TensorFlow Keras API -- Classification tasks and decision boundaries -- Logistic regression -- Logistic regression on the MNIST dataset -- Summary -- References -- Chapter 3: Convolutional Neural Networks -- Deep convolutional neural networks -- Local receptive fields -- Shared weights and bias -- A mathematical example -- ConvNets in TensorFlow -- Pooling layers -- Max pooling -- Average pooling -- ConvNets summary -- An example of DCNN: LeNet -- LeNet code in TF -- Understanding the power of deep learning -- Recognizing CIFAR-10 images with deep learning -- Improving the CIFAR-10 performance with a deeper network -- Improving the CIFAR-10 performance with data augmentation -- Predicting with CIFAR-10 -- Very deep convolutional networks for large-scale image recognition -- Recognizing cats with a VGG16 net work -- Utilizing the tf.Keras built-in VGG16 net module -- Recycling pre-built deep learning models for extracting features -- Deep Inception V3 for transfer learning -- Other CNN architectures -- AlexNet -- Residual networks -- HighwayNets and DenseNets -- Xception -- Style transfer -- Content distance -- Style distance -- Summary -- References -- Chapter 4: Word Embeddings -- Word embedding ‒ origins and fundamentals -- Distributed representations -- Static embeddings -- Word2Vec -- GloVe -- Creating your own embeddings using Gensim -- Exploring the embedding space with Gensim -- Using word embeddings for spam detection -- Getting the data -- Making the data ready for use -- Building the embedding matrix -- Defining the spam classifier -- Training and evaluating the model -- Running the spam detector -- Neural embeddings - not just for words -- Item2Vec -- node2vec -- Character and subword embeddings -- Dynamic embeddings -- Sentence and paragraph embeddings.…”
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Hybrid System Identification Theory and Algorithms for Learning Switching Models / Yazar: Lauer, Fabien, Bloch, Gérard

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