Search Results - (((((((ant OR mantis) OR wanting) OR makart) OR cantor) OR anne) OR share) OR hints) algorithms.

Advances in parallel computing technologies and applications

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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

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Business Hack : the Wealth Dragon Way to Build a Successful Business in the Digital Age. by Lee, John

Table of Contents: “…; Disrupting the Market; The Power of Algorithms; Beyond the Digital Age; Chapter 12 Don't Become a Human Bot!…”
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Principles of artificial neural networks by Graupe, Daniel

Table of Contents: “…Fundamentals of biological neural networks -- ch. 3. Basic principles of ANNs and their early structures. 3.1. Basic principles of ANN design. 3.2. …”
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Advances in intelligent transportation : system and technology : selected, peer reviewed papers from the 1st International Doctoral Annual Symposium on Intelligent Transportation T...

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Information engineering for mechanics and materials research

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Choice modelling : the state-of-the-art and the state-of-practice : proceedings from the inaugural International Choice Modelling Conference

Table of Contents: “…On estimation of hybrid choice models / Denis Bolduc, Ricardo Alvarez-Daziano -- A model of travel happiness and mode switching / Maya Abou-Zeid, Moshe Ben-Akiva -- On path generation algorithms for route choice models / Emma Frejinger, Michel Bierlaire -- Mode choice endogeneity in value of travel time estimation / Stefan L. …”
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Advanced Python Programming : Build High Performance, Concurrent, and Multi-Threaded Apps with Python Using Proven Design Patterns. by Lanaro, Gabriele

Table of Contents: “…Adding static typesVariables; Functions; Classes; Sharing declarations; Working with arrays; C arrays and pointers; NumPy arrays; Typed memoryviews; Particle simulator in Cython; Profiling Cython; Using Cython with Jupyter; Summary; Chapter 5: Exploring Compilers; Numba; First steps with Numba; Type specializations; Object mode versus native mode; Numba and NumPy; Universal functions with Numba; Generalized universal functions; JIT classes; Limitations in Numba; The PyPy project; Setting up PyPy; Running a particle simulator in PyPy; Other interesting projects; Summary…”
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Haptic Feedback Teleoperation of Optical Tweezers by Ni, Zhenjiang

Table of Contents: “…Specific designs for haptic interactions; 1.4.1. Temporal sharing; 1.4.2. Spatial sharing; 1.5. Discussion; 1.6. …”
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A cabinet of philosophical curiosities : a collection of puzzles, oddities, riddles, and dilemmas by Sorensen, Roy A.

Table of Contents: “…; Descartes's Disappearance; The Most Fairly Distributed Good; Fairness Framed; Towards a Fairer Share of Dishwashing; What the Dishwasher Missed; Developmental Self-Defeat; Random Quiz; Enforcing Gresham's Law; Gresham's Law of Numbers; Laziest Reductio.…”
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Machine Learning with Spark - Second Edition. by Dua, Rajdeep

Table of Contents: “…Generating predictions for the Kaggle/StumbleUpon evergreen classification dataset -- Evaluating the performance of classification models -- Accuracy and prediction error -- Precision and recall -- ROC curve and AUC -- Improving model performance and tuning parameters -- Feature standardization -- Additional features -- Using the correct form of data -- Tuning model parameters -- Linear models -- Iterations -- Step size -- Regularization -- Decision trees -- Tuning tree depth and impurity -- The naive Bayes model -- Cross-validation -- Summary -- Chapter 7: Building a Regression Model with Spark -- Types of regression models -- Least squares regression -- Decision trees for regression -- Evaluating the performance of regression models -- Mean Squared Error and Root Mean Squared Error -- Mean Absolute Error -- Root Mean Squared Log Error -- The R-squared coefficient -- Extracting the right features from your data -- Extracting features from the bike sharing dataset -- Training and using regression models -- BikeSharingExecutor -- Training a regression model on the bike sharing dataset -- Linear regression -- Generalized linear regression -- Decision tree regression -- Ensembles of trees -- Random forest regression -- Gradient boosted tree regression -- Improving model performance and tuning parameters -- Transforming the target variable -- Impact of training on log-transformed targets -- Tuning model parameters -- Creating training and testing sets to evaluate parameters -- Splitting data for Decision tree -- The impact of parameter settings for linear models -- Iterations -- Step size -- L2 regularization -- L1 regularization -- Intercept -- The impact of parameter settings for the decision tree -- Tree depth -- Maximum bins -- The impact of parameter settings for the Gradient Boosted Trees -- Iterations -- MaxBins -- Summary.…”
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World's greatest architect : making, meaning, and network culture by Mitchell, William J. (William John), 1944-2010

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OpenCV Android Programming By Example. by Muhammad, Amgad

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Apache Spark for Data Science Cookbook. by Chitturi, Padma Priya

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Cinder Creative Coding Cookbook. by Dawid Gorny, Rui Madeira

Table of Contents: “…Creating a simple video controllerSaving window content as an image; Saving window animations as video; Saving window content as a vector graphics image; Saving high resolution images with the tile renderer; Sharing graphics between applications; Building Particle Systems; Introduction; Creating a particle system in 2D; Applying repulsion and attraction forces; Simulating particles flying in the wind; Simulating flocking behavior; Making our particles sound reactive; Aligning particles to a processed image; Aligning particles to the mesh surface; Creating springs.…”
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Principles of Quantum Computation and Information, Volume I : Basic Concepts. by Casati, Giulio, Strini, Giuliano

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Frontiers of Artificial Intelligence in Medical Imaging. by Razmjooy, Navid

Table of Contents: “…5.5 Electromagnetic field optimization algorithm -- 5.6 Developed electromagnetic field optimization algorithm -- 5.7 Simulation results -- 5.7.1 Image acquisition -- 5.7.2 Pre-processing stage -- 5.7.3 Processing stage -- 5.7.4 Classification -- 5.8 Final evaluation -- 5.9 Conclusions -- References -- Chapter 6 Evaluation of COVID-19 lesion from CT scan slices: a study using entropy-based thresholding and DRLS segmentation -- 6.1 Introduction -- 6.2 Context -- 6.3 Methodology -- 6.3.1 COVID-19 database -- 6.3.2 Image conversion and pre-processing -- 6.3.3 Image thresholding…”
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Proceedings of the 2009 International Conference on Computer and Network Technology, Chennai, India, 24-26 July 2009

Table of Contents: “…An Ownership Sharing Protocol for RFID without a Trusted Third Party G. …”
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FRBR, before and after : a look at our bibliographic models by Coyle, Karen

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Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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