Search Results - (((((((ant OR kkantis) OR wantis) OR hints) OR cantor) OR anne) OR find) OR granting) algorithms.

Numerical Methods for Eigenvalue Problems. by Börm, Steffen

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Clojure for data science : statistics, big data, and machine learning for Clojure programmers by Garner, Henry

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Cryptography Apocalypse : Preparing for the Day When Quantum Computing Breaks Today's Crypto. by Grimes, Roger A.

Table of Contents: “…87 -- Is Peter Shor’s Algorithm Real? 88 -- Do We Have Enough Stable Qubits? …”
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Complexity : a guided tour by Mitchell, Melanie (Computer scientist)

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Dermatologic principles and practice in oncology : conditions of the skin, hair, and nails in cancer patients

Table of Contents: “…Borovicka, Jennifer R.S. Gordon, Ann Cameron Haley, Nicole E. Larson and Dennis P. …”
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Computational ecology : artificial neural networks and their applications by Zhang, Wenjun

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Infinite Products of Operators and Their Applications. by Reich, Simeon

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The birth of computer vision by Dobson, James E.

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Modeling semi-arid water-soil-vegetation systems by Wang, Xixi

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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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Node Web Development. by Herron, David, 1820-1900

Table of Contents: “…Npm -- the Node package managerStarting Node servers at system startup; Summary; Chapter 3: Node Modules; Defining a module; Node modules; Node's algorithm for resolving require(module); Module identifiers and path names; Local modules within your application; Bundling external dependencies with your application; System-wide modules in NODE_PATH and elsewhere; Complex modules -- modules as directories; Node package manager; The npm package format; Finding npm packages; Using the npm commands; Getting help with npm; Viewing package information; Installing an npm package.…”
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Building Machine Learning Systems with Python. by Richert, Willi

Table of Contents: “…A more complex dataset and a more complex classifierLearning about the Seeds dataset; Features and feature engineering; Nearest neighbor classification; Binary and multiclass classification; Summary; Chapter 3: Clustering -- Finding Related Posts; Measuring the relatedness of posts; How not to do it; How to do it; Preprocessing -- similarity measured as similar number of common words; Converting raw text into a bag-of-words; Counting words; Normalizing the word count vectors; Removing less important words; Stemming; Installing and using NLTK; Extending the vectorizer with NLTK's stemmer.…”
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Clinical Guide to Cardiology. by Camm, Christian Fielder

Table of Contents: “…Intro -- Clinical Guide to Cardiology -- Contents -- Contributors -- Acronyms and Abbreviations -- About the Companion Website -- PART 1 Examination Techniques -- 1 Examination Techniques -- 1.1 Common conditions to be looked for on the examination -- 1.2 Clinical examination -- peripheries -- 1.3 Clinical examination -- the praecordium -- 1.4 How to present your findings -- Safety first approach -- Ward-round based -- 1.5 Eponymous signs and symptoms -- PART 2 Approach to Presenting Complaints -- 2 Chest Pain -- 2.1 Definition -- 2.2 Diagnostic algorithm -- 2.3 Differentials list…”
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Moments, Positive Polynomials And Their Applications.

Table of Contents: “…Systems of Polynomial Equations -- 6.1 Introduction -- 6.2 Finding a Real Solution to Systems of Polynomial Equations -- 6.3 Finding All Complex and/or All Real Solutions: A Uni ed Treatment -- 6.4 Summary -- 6.5 Exercises -- 6.6 Notes and Sources -- 7. …”
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CompTIA security+ deluxe study guide : exam SY0-301 by Dulaney, Emmett A.

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A comprehensive guide on OpenCL Programming with examples by Banger, Ravishekhar

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Artificial vision : a clinical guide

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The AI delusion by Smith, Gary

Table of Contents: “…If you torture the data long enough; Mendel; The Texas sharpshooter fallacy; Data mining; QuickStop; Torturing data; Retroactive recall; Money priming; Seek and you will find; The Laugher Curve; It's not you, it's me; Great to good.…”
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Deep learning for dummies by Mueller, John, 1958-, Massaron, Luca

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Robust and error-free geometric computing by Eberly, Dave

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