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SPIRES-BOOKS: FIND KEYWORD PYTHON *END*INIT* use /tmp/qspiwww.webspi1/16798.20 QRY 131.225.70.96 . find keyword python ( in books using www Cover
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Call number:9781783553365:ONLINE Show nearby items on shelf
Title:Python Data Analysis learn how to apply powerful data analysis techniques with popular open source Python modules
Author(s): Ivan Idris
Date:2014
Publisher:Birmingham, UK: Packt Publishing
Size:348 p
Note:online access: non linear lending
Contents:Getting started with Python libraries -- NumPy arrays -- Statistics and linear algebra -- pandas primer -- Retrieving, processing, and storing data -- Data visualization -- Signal processing and time series -- Working with databases -- Analyzing tex tual data and social media -- Predictive analytics and machine learning -- Environments outside the Python ecosystem and cloud computing -- Performance tuning, profiling, and concurrency -- Appendix A : key concepts -- Appendix B : useful functions -- Ap p endix C : online resources
ISBN:9781783553365
Series:eBooks
Series:EBL eBook
Keywords: Python (Computer program language)
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Call number:9781491904404:ONLINE Show nearby items on shelf
Title:Data science from scratch: first principles with Pylon
Author(s): Joel Grus
Date:2015
Publisher:Sebastopol, CA: O'Reilly Media
Size:1 online resource (330 p)
Note:single concurrent user
ISBN:9781491904404
Series:eBooks
Series:ebrary eBook
Keywords: Python (Computer program language)
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Call number:9781449323615:ONLINE Show nearby items on shelf
Title:Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython
Author(s): Wes McKinney
Date:2012
Publisher:O'Reilly Media
Size:469 p
Contents:Preliminaries -- Introductory examples -- IPython : an interactive computing development environment -- NumPy basics : arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data wrangling : clean, transform, merge, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Financial and economic data applications -- Advanced NumPy
ISBN:9781449319793
Series:eBooks
Keywords: Data mining , Programming languages (Electronic computers) , Python (Computer program language)
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Call number:1786301261:ONLINE Show nearby items on shelf
Title:Digital Signal Processing (DSP) with Python Programming
Author(s): Charbit
Date:2017
Publisher:Wiley-ISTE
Size:1 online resource (291 p.)
ISBN:9781786301260
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:1118961749:ONLINE Show nearby items on shelf
Title:Machine Learning in Python:for Predictive Analysis
Author(s): Bowles
Date:2015
Publisher:Wiley
Size:1 online resource (361 p.)
ISBN:9781118961742
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Computer Science
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Call number:111890866X:ONLINE Show nearby items on shelf
Title:Python Projects
Author(s): Cassell
Date:2014
Publisher:Wrox
Size:1 online resource (385 p.)
ISBN:9781118908662
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Computer Science
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Call number:SPRINGER-2016-9783662498873:ONLINE Show nearby items on shelf
Title:A Primer on Scientific Programming with Python
Author(s): Hans Petter Langtangen
Date:2016
Edition:5th ed. 2016
Size:1 online resource (20 p.)
Note:10.1007/978-3-662-49887-3
Contents:Preface -- Computing with Formulas -- Loops and Lists -- Functions and Branching -- User Input and Error Handling -- Array Computing and Curve Plotting -- Dictionaries and Strings -- Introduction to Classes -- Random Numbers and Simple Games -- Obj ect-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus -- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Migrating Py thon to Compiled Code -- Technical Topics -- References -- Index
ISBN:9783662498873
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Texts in Computational Science and Engineering: 6
Keywords: Mathematics , Computer programming , Computer science , Computer mathematics , Physics , Mathematics , Computational Science and Engineering , Programming Techniques , Mathematics of Computing , Numerical and Computational Physics
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Call number:SPRINGER-2016-9783319324289:ONLINE Show nearby items on shelf
Title:Programming for Computations - Python A Gentle Introduction to Numerical Simulations with Python
Author(s): Svein Linge
Date:2016
Size:1 online resource (232 p.)
Note:10.1007/978-3-319-32428-9
Contents:Preface -- The first few steps -- Basic constructions -- Computing integrals -- Solving ordinary differential equations -- Solving partial differential equations -- Solving nonlinear algebraic equations -- Getting access to Python -- References -- Index
ISBN:9783319324289
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Texts in Computational Science and Engineering: 15
Keywords: Mathematics , Numerical analysis , Computer mathematics , Computer software , Mathematics , Computational Science and Engineering , Numeric Computing , Mathematical Software , Numerical Analysis
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Call number:SPRINGER-2016-9783319283166:ONLINE Show nearby items on shelf
Title:An Introduction to Statistics with Python With Applications in the Life Sciences
Author(s): Thomas Haslwanter
Date:2016
Size:1 online resource (85 p.)
Note:10.1007/978-3-319-28316-6
Contents:Part I: Python and Statistics -- Why Statistics? -- Python -- Data Input -- Display of Statistical Data -- Part II: Distributions and Hypothesis Tests -- Background -- Distributions of One Variable -- Hypothesis Tests -- Tests of Means of Numerical Data -- Tests on Categorical Data -- Analysis of Survival Times -- Part III: Statistical Modelling -- Linear Regression Models -- Multivariate Data Analysis -- Tests on Discrete Data -- Bayesian Statistics -- Solutions -- Glossary -- Index
ISBN:9783319283166
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Programming languages (Electronic computers) , Biostatistics , Computer mathematics , Statistics , Statistics and Computing/Statistics Programs , Statistics for Life Sciences, Medicine, Health Sciences , Biostatistics , Computational Science and Engineering , Programming Languages, Compilers, Interpreters
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Call number:SPRINGER-2014-9783642549595:ONLINE Show nearby items on shelf
Title:A Primer on Scientific Programming with Python [electronic resource]
Author(s): Hans Petter Langtangen
Date:2014
Edition:4th ed. 2014
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics,numerical calculus, st atistics, physics, biology and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageousto study classical and numerical one-variable c alculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of scienceand engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objectsand functions and embracing the object-oriented paradigm. Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python on the streets could be alittle jealous of students who have the opportunity to take a course out of Langtangens Primer. John D. Cook, The Mathematical Association of Am erica, September 2011 This book goes through Python in particular, and programmingin general, via tasks that scientists will likely perform. It contains valuable informationfor students new to scientific computing and would be the perfect bridge between a n introduction to programming and an advanced course onnumerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March/April 2012
Contents:Preface
Computing with Formulas
Loops and Lists
Functions and Branching
User Input and Error Handling
Array Computing and Curve Plotting
Dictionaries and Strings
Introduction to Classes
Random Numbers and Simple Games
Object
Oriented Programming
Sequences and Difference Equations
Introduction to Discrete Calculus
Introduction to Differential Equations
A Complete Differential Equation Project
Programming of Differential Equations
Debugging
Migrating Python to Compiled Code
Technical Topics
Bibliography
Index
ISBN:9783642549595
Series:eBooks
Series:SpringerLink
Series:Texts in Computational Science and Engineering, 1611-0994 : v6
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science
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Call number:SPRINGER-2012-9783642302930:ONLINE Show nearby items on shelf
Title:A Primer on Scientific Programming with Python [electronic resource]
Author(s): Hans Petter Langtangen
Date:2012
Edition:3rd ed. 2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics,numerical calculus, s tatistics, physics, biology, and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it isadvantageous to study classical and numerical one-variabl e calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in variousbranches of science and engineering, with the aid of numerical methods and programmi ng. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.
Note:Springer eBooks
Contents:Preface
Computing with Formulas
Loops and Lists
Functions and Branching
Input Data and Error Handling
Array Computing and Curve Plotting
Files, Strings and Dictionaries
Introduction to Classes
Random Numbers and Simple Games
Object
Oriented Programming
Sequences and Difference Equations
Introduction to Discrete Calculus
Introduction to Differential Equations
A Complete Differential Equation Project
Programming of Differential Equations
Debugging
Migrating Python to Compiled Code
Technical Topics
Bibliography
Index
ISBN:9783642302930
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Computational Science and Engineering, 1611-0994 : v6
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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Call number:SPRINGER-2012-9781461432265:ONLINE Show nearby items on shelf
Title:Pyomo Optimization Modeling in Python [electronic resource]
Author(s): William E Hart
Carl Laird
Jean-Paul Watson
David L Woodruff
Date:2012
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book provides a complete and comprehensive guide to Pyomo(Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, andpractitioners. Modeling is a fundamental process in many aspects of scientific research, engineering, and business. This text beautifully illustrates the breadth of the modeling capabilities that are supported by this new software andits handling of complex real-world applications . Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (AlgebraicModeling Language) tools.Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language.Python is a powerful and dynamic programming language that has a very clear, readable syntaxand intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parame ters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can beused from a command-line interface and within Python's interactive command environment, which makes it easy to create P yomo models, apply a variety of optimizers, and examine solutions. The text begins with a tutorial on simplelinear and integer programming models. Information needed to install and get started with the software is also provided. A detailed reference of P yomo's modeling components is illustrated with extensive examples, including a discussionof how to load data from sources like spreadsheets and databases. The final chapters cover advanced topics such as nonlinear models, stochastic models, and scripting examples
Note:Springer eBooks
Contents:Preface
1. Introduction
2. Pyomo Modeling Strategies
3. Model Components: Variables, Objectives and Constraints
4. Model Components: Sets and Parameters
5. Mischellaneous Model Components and Utility Functions
6. Initializing Abstract Models with Data Command Files
7. The Pyomo Command
Line Interface
8. Nonlinear Programming with Pyomo
9. Stochastic Programming Extensions
10. Scripting and Algorithm Development
A. Installing Coopr
B. A Brief Python Tutorial
C. Pyomo and Coopr: The Bigger Picture
Index
ISBN:9781461432265
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v67
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer science , Computer simulation , Computer science Mathematics , Computer software , Mathematical optimization
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Call number:SPRINGER-2011-9783642183669:ONLINE Show nearby items on shelf
Title:A Primer on Scientific Programming with Python [electronic resource]
Author(s): Hans Petter Langtangen
Date:2011
Edition:2nd Edition
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics,numerical calculus, s tatistics, physics, biology, and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it isadvantageous to study classical and numerical one-variabl e calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in variousbranches of science and engineering, with the aid of numerical methods and programmi ng. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science
Note:Springer eBooks
Contents:Computing with Formulas
Loops and Lists
Functions and Branching
Input Data and Error Handling
Array Computing and Curve Plotting
Files, Strings and Dictionaries
Introduction to Classes
Random Numbers and Simple Games
Object
Oriented Programming
Sequences and Difference Equations
Introduction to Discrete Calculus
Introduction to Differential Equations
A Complete Differential Equation Project
Programming of Differential Equations
Debugging
TechnicalTopics
Bibliography
Index
ISBN:9783642183669
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Computational Science and Engineering, 1611-0994 : v6
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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Call number:SPRINGER-2009-9783642024757:ONLINE Show nearby items on shelf
Title:A Primer on Scientific Programming with Python [electronic resource]
Author(s): Hans Petter Langtangen
Date:2009
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics,numerical calculus, s tatistics, physics, biology, and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it isadvantageous to study classical and numerical one-variabl e calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in variousbranches of science and engineering, with the aid of numerical methods and programmi ng. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science
Note:Springer eBooks
ISBN:9783642024757
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Computational Science and Engineering, 1611-0994 : v6
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science
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Call number:SPRINGER-2008-9783540739166:ONLINE Show nearby items on shelf
Title:Python Scripting for Computational Science [electronic resource]
Author(s): Hans Petter Langtangen
Date:2008
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The goal of this book is to teach computational scientists how to develop tailored, flexible, and human-efficient working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python.The focus is on exampl es and applications of relevance to computational scientists: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization steering simulations and computationalexperiments equipping old programs with graphical user interfaces making computational Web applications and creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran. In short,scripting with Python makes you much more productive, increases the reliabili ty of your scientific work and lets you have more fun - on Unix, Windows and Macintosh. All the tools and examples in this book are open source codes. Thethird edition is compatible with the new NumPy implementation and features updated information, corre ction of errors, and improved associated software tools
Note:Springer eBooks
ISBN:9783540739166
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Computational Science and Engineering, 1611-0994 : v3
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science , Engineering
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Call number:SPRINGER-2006-9783540312697:ONLINE Show nearby items on shelf
Title:Python Scripting for Computational Science [electronic resource]
Author(s): Hans Petter Langtangen
Date:2006
Edition:Second Edition
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The goal of this book is to teach computational scientists how to develop tailored, flexible, and human-efficient working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python.The focus is on exampl es and applications of relevance to computational scientists: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization steering simulations and computationalexperiments equipping old programs with graphical user interfaces making computational Web applications and creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran. In short,scripting with Python makes you much more productive, increases the reliabili ty of your scientific work and lets you have more fun - on Unix, Windows and Macintosh. All the tools and examples in this book are open source codes. Thethird edition is compatible with the new NumPy implementation and features updated information, corre ction of errors, and improved associated software tools
Note:Springer eBooks
ISBN:9783540312697
Series:e-books
Series:SpringerLink (Online service)
Series:Texts in Computational Science and Engineering, 1611-0994 : v3
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Software engineering , Computer science
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Call number:SPRINGER-2004-9783662054505:ONLINE Show nearby items on shelf
Title:Python Scripting for Computational Science
Author(s): Hans Petter Langtangen
Date:2004
Size:1 online resource (732 p.)
Note:10.1007/978-3-662-05450-5
Contents:1 Introduction -- 2 Getting Started with Python Scripting -- 3 Basic Python -- 4 Numerical Computing in Python -- 5 Combining Python with Fortran, C, and C++ -- 6 Introduction to GUI Programming -- 7 Web Interfaces and CGI Programming
-- 8 Advanced Python -- 9 Fortran Programming with NumPy Arrays -- 10 C and C++ Programming with NumPy Arrays -- 11 More Advanced GUI Programming -- 12 Tools and Examples -- A Setting up the Required Software Environment -- A.1
Installation on Unix Systems -- A.1.1 A Suggested Directory Structure -- A.1.2 Setting Some Environment Variables -- A.1.3 Installing Tcl/Tk and Additional Modules -- A.1.4 Installing Python -- A.1.5 Installing Python Modules -- A.1.6
Installing Gnuplot -- A.1.7 Installing SWIG -- A.1.8 Summary of Environment Variables -- A.1.9 Testing the Installation of Scripting Utilities -- A.2 Installation on Windows Systems -- B Elements of Software Engineering -- B.1 Building
and Using Modules -- B.1.1 Single-File Modules -- B.1.2 Multi-File Modules -- B.1.3 Debugging and Troubleshooting -- B.2 Tools for Documenting Python Software -- B.2.1 Doc Strings -- B.2.2 Tools for Automatic Documentation -- B.3
Coding Standards -- B.3.1 Style Guide -- B.3.2 Pythonic Programming -- B.4 Verification of Scripts -- B.4.1 Automating Regression Tests -- B.4.2 Implementing a Tool for Regression Tests -- B.4.3 Writing a Test Script -- B.4.4 Verifying
Output from Numerical Computations -- B.4.5 Automatic Doc String Testing -- B.4.6 Unit Testing -- B.5 Version Control Management -- B.5.1 Getting Started with CVS -- B.5.2 Building Scripts to Simplify the Use of CVS -- B.6 Exercises
ISBN:9783662054505
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Texts in Computational Science and Engineering: 3
Keywords: Mathematics , Software engineering , Computer mathematics , Physics , Computational intelligence , Mathematics , Computational Science and Engineering , Numerical and Computational Physics , Software Engineering/Programming and Operating Systems , Computational Intelligence
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Call number:SPRINGER-2003-9783642182372:ONLINE Show nearby items on shelf
Title:Advanced Topics in Computational Partial Differential Equations Numerical Methods and Diffpack Programming
Author(s):
Date:2003
Size:1 online resource (663 p.)
Note:10.1007/978-3-642-18237-2
Contents:1 Parallel Computing -- 1.1 Introduction to Parallel Computing -- 1.2 A Different Performance Model -- 1.3 The First MPI Encounter -- 1.4 Basic Parallel Programming with Diffpack -- 1.5 Parallelizing Explicit FD Schemes -- 1.6
Parallelizing FE Computations on Unstructured Grids -- References -- Overlapping Domain Decomposition Methods -- 2.1 Introduction -- 2.2 The Mathematical Formulations -- 2.3 A 1D Example -- 2.4 Some Important Issues -- 2.5 Components
of Overlapping DD Methods -- 2.6 A Generic Implementation Framework -- 2.7 Parallel Overlapping DD Methods -- 2.8 Two Application Examples -- References -- 3 Software Tools for Multigrid Methods -- 3.1 Introduction -- 3.2 Sketch of How
Multilevel Methods are Implemented in Diffpack -- 3.3 Implementing Multigrid Methods -- 3.4 Setting up an Input File -- 3.5 Playing Around with Multigrid -- 3.6 Equipping the Poisson2 Solver with Multigrid -- 3.7 Systems of Equations,
Linear Elasticity -- 3.8 Nonlinear Problems -- References -- 4 Mixed Finite Elements -- 4.1 Introduction -- 4.2 Model Problems -- 4.3 Mixed Formulation -- 4.4 Some Basic Concepts of a Finite Element -- 4.5 Some Code Examples -- 4.6
Programming with Mixed Finite Elements in a Simulator -- References -- 5 Systems of PDEs and Block Preconditioning -- 5.1 Introduction -- 5.2 Block Preconditioners in General -- 5.3 The Bidomain Equations -- 5.4 Two Saddle Point
Problems -- References -- 6 Fully Implicit Methods for Systems of PDEs -- 6.1 Introduction -- 6.2 Implementation of Solvers for PDE Systems in Diffpack -- 6.3 Problem with the Gauss-Seidel Method, by Example -- 6.4 Fully Implicit
Implementation -- 6.5 Applications -- 6.6 Conclusion -- References -- 7 Stochastic Partial Differential Equations -- 7.1 Introduction -- 7.2 Some Simple Examples -- 7.3 Solution Methods -- 7.4 Quick Overview of Diffpack Tools -- 7.5
Tools for Random Variables -- 7.6 Diffpack Tools for Random Fields -- 7.7 Summary -- 7.A Transformation of Random Variables -- 7.B Implementing a New Distribution -- References -- 8 Using Diffpack from Python Scripts -- 8.1
Introduction -- 8.2 Developing Python Interfaces to C/C++ Functions -- 8.3 Compiling and Linking Wrapper Code with Diffpack -- 8.4 Converting Data between Diffpack and Python -- 8.5 Building an Interface to a More Advanced Simulator --
8.6 Installing Python, SWIG etc -- 8.7 Concluding Remarks -- References -- 9 Performance Modeling of PDE Solvers -- 9.1 Introduction -- 9.2 Model Problems -- 9.3 Numerical Methods -- 9.4 Total CPU Time Consumption -- 9.5 Solution of
Linear Systems -- 9.6 Construction of Linear Systems -- 9.7 Concluding Remarks -- References -- 10 Electrical Activity in the Human Heart -- 10.1 The Basic Physiology -- 10.2 Outline of a Mathematical Model -- 10.3 The Bidomain Model
-- 10.4 A Complete Mathematical Model -- 10.5 Physiology of the Heart Muscle Tissue -- 10.6 The Numerical Method -- 10.7 Implementation -- 10.8 Optimization of the Simulator -- 10.9 Simulation Results -- 10.10 Concluding Remarks --
References -- 11 Mathematical Models of Financial Derivatives -- 11.1 Introduction -- 11.2 Basic Assumptions -- 11.3 Forwards and Futures -- 11.4 The Black-Scholes Analysis -- 11.5 European Call and Put Options -- 11.6 American Options
-- 11.7 Exotic Options -- 11.8 Hedging -- 11.9 Remarks -- References -- 12 Numerical Methods for Financial Derivatives -- 12.1 Introduction -- 12.2 Model Summary -- 12.3 Monte-Carlo Methods -- 12.4 Lattice Methods -- 12.5 Finite
Difference Methods -- 12.6 Finite Element Methods -- References -- 13 Finite Element Modeling of Elastic Structures -- 13.1 Introduction -- 13.2 An Introductory Example Bar Elements -- 13.3 Another Example Beam Elements -- 13.4 General
Three-Dimensional Elasticity -- 13.5 Degrees of Freedom and Basis Functions -- 13.6 Material Types and Elasticity Matrices -- 13.7 Element Matrices in Local Coordinates -- 13.8 Element Load Vectors in Local Coordinates -- 13.9 Element
Matrices and Vectors in Global Coordinates -- 13.10 Element Forces, Stresses, and Strains -- 13.11 Implementation of Structural Elements -- 13.12 Some Example Programs -- 13.13 Test Problems -- 13.14 Summary -- References -- 14
Simulation of Aluminum Extrusion -- 14.1 Introduction -- 14.2 Mathematical Formulation -- 14.3 Finite Element Implementation -- 14.4 Object-Oriented Implementation -- 14.5 Numerical Experiments -- 14.6 Concluding Remarks -- References
-- 15 Simulation of Sedimentary Basins -- 15.1 Introduction -- 15.2 The Geomechanical and Mathematical Problem -- 15.3 Numerical Methods -- 15.4 Implementing a Solver for a System of PDEs -- 15.5 Verification -- 15.6 A Magmatic Sill
Intrusion Case Study -- 15.7 Concluding Remarks -- References
ISBN:9783642182372
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Lecture Notes in Computational Science and Engineering: 33
Keywords: Mathematics , Mathematical analysis , Analysis (Mathematics) , Partial differential equations , Computer mathematics , Mathematics , Analysis , Computational Science and Engineering , Partial Differential Equations
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Call number:SPRINGER-2002-9783642562402:ONLINE Show nearby items on shelf
Title:Multimedia Tools for Communicating Mathematics
Author(s):
Date:2002
Size:1 online resource (314 p.)
Note:10.1007/978-3-642-56240-2
Contents:1 Computer Animated Mathematics Videotapes -- 2 A Virtual Reconstruction of a Virtual Exhibit -- 3 An Intuitive Approach to Elementary Mathematics on the Web -- 4 OpenMath Technology for Interactive Mathematical Documents -- 5 The
StageTools Package for Creating Geometry for the Web -- 6 Communicating and Learning Mathematics with Hypervideo -- 7 Collaboration in a Multimedia Laboratory -- 8 jDvi — A Way to Put Interactive TeX on the Web -- 9 Visual Calculus —
Development and Tools -- Color Plates -- 10 EG-Models — A New Journal for Digital Geometry Models -- 11 The Future of Mathematical Software -- 12 A Dynamic Setup for Elementary Geometry -- 13 Dynamic Geometry on WWW -- 14 Minimalistic
Tools for Mathematical Multimedia -- 15 Publication of Interactive Visualizations with JavaView -- 16 The Solver Learning Environment for Solving Mathematical Word Problems: Pupils’ Discussions -- 17 Interactive Knot Theory with Knot
Plot -- 18 Developing Gato and CATBox with Python: Teaching Graph Algorithms through Visualization Experimentation -- 19 Rescalable Real-Time Interactive Computer Animations
ISBN:9783642562402
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Computer science , Software engineering , Multimedia information systems , Application software , Mathematics , Visualization , Computer Science , Computer Applications , Mathematics, general , Software Engineering/Programming and Operating Systems , Visualization , Multimedia Information Systems
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Title:Machine learning in python: Essential techniques for predictive analysis
Author(s): Michael Bowles
Date:2015
Publisher:Indianapolis, IN: John Wiley & Sons
Size:326 p.
Contents:The two essential algorithms for making predictions -- Understand the problem by understanding the data -- Predictive model building : balancing performance, complexity, and big data -- Penalized linear regression -- Building predictive models using p enalized linear methods -- Ensemble methods -- Building ensemble models with Python.
ISBN:9781118961742
Keywords: Machine learning , Python (Computer program language)
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Call number:QC793.47.E4R66::2005 Show nearby items on shelf
Title:ROOT An Object-oriented data analysis framework: Users Guide 4.04
Author(s):
Date:2005
Edition:4.04
Size:393 pgs
Contents:1. Introduction, 2. Getting Started, 3. Histograms, 4. Graphs, 5. Fitting Histograms, 6. A Little C++, 7. CINT the C++ Interpreter, 8. Object Ownership, 9. Graphics and the Graphical User Interface, 10. Folders and Tasks, 11. Input/Output, 12. Trees, 13. Linear Algebra in Root, 14. Adding a Class, 15. Collection Classes, 16. Physics Vectors, 17. The Geometry Package, 18. Python and Ruby Interfaces, 19. The Tutorials and Tests, 20. Example Analysis, 21. Networking, 22. Threads, 23. PROOF: Parallel Processing, 24. Writing a Graphical User Interface, 25. Automatic HTML Documentation, 26. Appendix: Install and Build ROOT
Keywords: Particles (Nuclear physics) Data processing
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Title:Computational physics
Author(s): M. E. J. Newman
Date:2012
Publisher:Createspace
Size:549 p
Contents:Introduction -- Python programming for physicists -- Graphics and visualization -- Accuracy and speed -- Integrals and derivatives -- Solution of linear and nonlinear equations -- Fourier transforms -- Ordinary differential equations -- Partial diff erential equations -- Random processes and Monte Carlo methods -- Using what you have learned
ISBN:9781480145511
Keywords: Physics Data processing. , Python (Computer program language)
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Title:Statistics, data mining, and machine learning in astronomy A practical python guide for the analysis of survey data
Author(s): Zeljko Ivezic
Andrew Connolly
Jacob T VanderPlas
Alexander Gray
Date:2014
Publisher:Princeton, N.J. : Princeton University Press
Size:540 p.
ISBN:9780691151687
Series:Princeton series in modern observational astronomy
Keywords: Astronomy, Data processing , Statistical astronomy
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Title:NumPy beginner's guide: an action packed guide using real world examples of the easy to use, high performance, free open source NumPy mathematical library
Author(s): Ivan. Idris
Date:2014
Edition:2nd ed
Publisher:Birmingham :Packt Pub
Size:287 p
Contents:NumPy quick start -- Beginning with NumPy fundamentals -- Get in terms with commonly used functions -- Convenience functions for your convenience -- Working with matrices and ufuncs -- Move further with NumPy modules -- Peeking into special rountine s -- Assure quality with testing -- Plotting with Matplotlib -- When NumPy is not enough--SciPy and beyond -- Playing with Pygame.
ISBN:9781782166085
Keywords: Mathematics, Data processing. , Python (Computer program language) , Mathematical analysis.
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Call number:QA76.9.U83S89::2008 Show nearby items on shelf
Title:Rapid GUI programming with Python and Qt: The definitive guide to PyQt programming
Author(s): Mark Summerfield
Date:2008
Publisher:Upper Saddle River, NJ: Prentice Hall
Size:625 p.
Contents:pt. I. Python programming -- Data types and data structures -- Control structures -- Classes and modules -- pt. II. Basic GUI programming -- Introduction to GUI programming -- Dialogs -- Main windows -- Using Qt designer -- Data handling and custom fi le formats -- pt. III. Intermediate GUI programming -- Layouts and multiple documents -- Events, the clipboard, and drag and drop -- Custom widgets -- Item-based graphics -- Rich text and printing -- Model/view programming -- Databases -- pt. IV. Advanced GUI programming -- Advanced model/view programming -- Online help and internationalization -- Networking -- Multithreading -- Appendix A. Installing -- Appendix B. Selected PyQt widgets -- Appendix C. Selected PyQt class hierarchies
ISBN:9780132354189
Series:Prentice Hall open source software development series
Keywords: Qt (Electronic resource) , Graphical user interfaces (Computer systems) , Python (Computer program language)
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Call number:QA76.9.D3P58::2010 Show nearby items on shelf
Title:The definitive guide to MongoDB: the NoSQL database for cloud and desktop computing
Author(s): Eelco Plugge
Peter Membrey
Tim Hawkins
Date:2010
Publisher:New York, NY : Apress
Size:307 p
Contents:Introduction to MongoDB, Installing MongoDB, The Data Model, Working with Data, GridFS, PHP and MongoDB, Python and MongoDB, Creating a Blog Application with the PHP Driver, Database Administration, Optimization, Replication, Sharding
ISBN:9781430230519
Keywords: Open source software. , Object-oriented databases.
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Call number:QA76.9.C65G665::2017 Show nearby items on shelf
Title:Introduction to Modeling and Simulation with MATLAB and Python
Author(s): Steven I. Gordon
Date:2017
Publisher:Chapman and Hall - CRC
ISBN:9781498773874
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Call number:QA76.73P98D22 Show nearby items on shelf
Title:Matplotlib plotting cookbook : learn how to create professional scientific plots using matplotlib, with more than 60 recipes that cover common use cases
Author(s): Alexandre Devert
Date:2014
Publisher:Birmingham, UK : Packt Publishing
Size:205 p
Contents:First steps -- Customizing the color and styles -- Working with annotations -- Working with figures -- Working with a file output -- Working with maps -- Working with 3D figures -- User interface.
ISBN:9781849513265
Keywords: Charts, diagrams, etc. , Python (Computer program language)
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Call number:QA76.73.V2:2012 Show nearby items on shelf
Title:Python Interview Questions You'll Most Likely Be Asked
Author(s):
Date:2012
Publisher:Vibrant Publishers:
Size:108 p
Contents:General Python Concepts, Python Looping, Python Conditionals, String Manipulation, Python Data Types, File Manipulation, Python Thread Management, Python Database Interface, Python Internet Communication, HTML/XML in Python, HR Questions
ISBN:9781463590222
Keywords: Python Interview Questions
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Call number:QA76.73.P98W38::1996 Show nearby items on shelf
Title:Internet programming with Python
Author(s): Aaron Watters
Guido Van Rossum
Date:1996
Publisher:M&T Books, New York
Size:477 p
ISBN:1558514848
Keywords: Python (Computer program language)
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Call number:QA76.73.P98V35::2009 Show nearby items on shelf
Title:Beginning Python Visualization : Crafting Visual Transformation Scripts
Author(s): Shai Vaingast
Date:2009
Publisher:Apress
ISBN:9781430218432
Series:The Expert's Voice in Open Source
Keywords: Python (Computer Program Language) , Object-Oriented Programming (Computer Science)
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Call number:QA76.73.P98S57::2015 Show nearby items on shelf
Title:Effective Python : 59 specific ways to write better Python
Author(s): Brett Slatkin
Date:2015
Publisher:Upper Saddle River, NJ : $b Addison-Wesley
Size:227 p
Contents:Pythonic thinking -- Functions -- Classes and inheritance -- Metaclasses and attributes -- Concurrency and parallelism -- Built-in modules -- Collaboration -- Production
ISBN:9780134034287
Keywords: Computer programming , Python (Computer program language)
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Call number:QA76.73.P98R36::2015 Show nearby items on shelf
Title:Fluent Python
Author(s): Luciano Ramalho
Date:2015
Edition:First edition
Publisher:O'Reilly
Size:765 p
Contents:The Python data model -- An array of sequences -- Dictionaries and stes -- Text versus bytes -- First-class functions -- Design patterns with first-class functions -- Function decorators and closures -- Object references, mutability, and recycling - - A pythonic object -- Sequence hacking, hashing, and slicing -- Interfaces: from protocols to ABCs -- Inheritance: for good or for worse -- Operator overloading: doing it right -- Iterables, iterators, and generators -- Context managers and else blocks - - Coroutines -- Concurrency with futures -- Concurrency with asyncio -- Dynamic attributes and properties -- Attribute descriptors -- Class metaprogramming.
ISBN:9781491946008
Keywords: Object-oriented programming languages , Python
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Call number:QA76.73.P98P95::2005 Show nearby items on shelf
Title:Python cookbook
Author(s): Alex Martelli (ed)
Anna Martelli Ravenscroft (ed.)
David Ascher (ed)
Date:2005
Publisher:O'Reilly
Note:2nd ed.
ISBN:0596007973
Keywords: Python (Computer program language)
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Call number:QA76.73.P98P56::2009 Show nearby items on shelf
Title:Dive into Python - A Guide to the Python Language for Programmers
Author(s): Mark Pilgrim
Date:2009
Publisher:Published by SoHo Books under the terms of the GNU Free Documentation Licence, v1.1
ISBN:9781441413024
Keywords: Python (Computer Program Language) , Object-Oriented Programming (Computer Science)
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Call number:QA76.73.P98M42::2013 Show nearby items on shelf
Title:Python for data analysis
Author(s): Wes McKinney
Julie Steele (ed.)
Meghan Blanchette (ed.)
Date:2013
Publisher:Beijing: O'Reilly
Contents:Preliminaries -- Introductory examples -- IPython : an interactive computing and development environment -- NumPy basics : arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data wrangling : clean, transform, merge, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Financial and economic data applications -- Advancded NumPy
ISBN:9781449319793
Keywords: Python (Computer program language) , Programming languages (Electronic computers) , Data mining.
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Call number:QA76.73.P98M33::2009 Show nearby items on shelf
Title:Scientific Scripting with Python
Author(s): Drew (Drew Alexander) McCormack
Date:2009
Publisher:[Morrisvill, NC] : www.lulu.com (Self-Published)
ISBN:9780557187225
Keywords: Python (Computer Program Language) , Programming Languages , Science - Data Processing
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Call number:QA76.73.P98M27::2003 Show nearby items on shelf
Title:Python in a nutshell
Author(s): Alex Martelli
Date:2003
Edition:1st ed.
Publisher:O'Reilly, Beijing
Size:636
ISBN:0596001886
Keywords: Python (Computer program language)
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Call number:QA76.73.P98L88::2006 Show nearby items on shelf
Title:Programming Python
Author(s): Mark Lutz
Date:2006
Publisher:O'Reilly
Note:3rd.ed.
ISBN:0596009259
Keywords: Python (Computer Program Language)
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Call number:QA76.73.P98L877::2013 Show nearby items on shelf
Title:Learning Python
Author(s): Mark Lutz
Date:2013
Edition:5th ed.
Publisher:O'Reilly: Sebastopol, CA
Size:1600 p
Note:Previous edition: 2009
Contents:Dedication Preface Getting Started Chapter 1: A Python Q&A Session Chapter 2: How Python Runs Programs Chapter 3: How You Run Programs Types and Operations Chapter 4: Introducing Python Object Types Chapter 5: Numeric Types Chapter 6: The Dynamic Ty ping Interlude Chapter 7: String Fundamentals Chapter 8: Lists and Dictionaries Chapter 9: Tuples, Files, and Everything ElseStatements and Syntax Chapter 10: Introducing Python Statements Chapter 11: Assignments, Expressions, and PrintsChapter 12: if Tes ts and Syntax RulesChapter 13: while and for LoopsChapter 14: Iterations and Comprehensions Chapter 15: The Documentation InterludeFunctions and Generators Chapter 16: Function Basics Chapter 17: Scopes Chapter 18: Arguments Chapter 19: Advanced Function Topics Chapter 20: Comprehensions and Generations Chapter 21: The Benchmarking Interlude Modules and Packages Chapter 22: Modules: The Big Picture Chapter 23: Module Coding Basics Chapter 24: Module Packages Chapter 25: Advanced Module Topics Classes and OOP Chapter 26: OOP: The Big Picture Chapter 27: Class Coding Basics Chapter 28: A More Realistic Example Chapter 29: Class Coding Details Chapter 30: Operator Overloading Chapter 31: Designing with Classes Chapter 32: Advanced Class Topics Exceptions and Tools Chapter 33: Exception Basics Chapter 34: Exception Coding Details Chapter 35: Exception Objects Chapter 36: Designing with Exceptions Advanced Topics Chapter 37: Unicode and Byte Strings Chapter 38: Managed Attributes Chapter 39: Decorators Chapter 40: Metaclasses Chapter 41: All Good Things
ISBN:9781449355739
Keywords: Python (Computer program language) , Object-oriented programming (Computer science)
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Call number:QA76.73.P98L877::2009 Show nearby items on shelf
Title:Learning Python
Author(s): Mark Lutz
Date:2009
Publisher:O'Reilly, Sebastopol, CA
Note:4TH ed.
ISBN:9780596158064
Keywords: Python (Computer Program Language) , Object-Oriented Programming (Computer Science)
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Call number:QA76.73.P98L877::2008 Show nearby items on shelf
Title:Learning Python
Author(s): Mark Lutz
Date:2008
Publisher:O'Reilly, Sebastopol, CA
Note:3rd ed.
ISBN:0596513984
Keywords: Python (Computer program language) , Object-oriented programming (Computer science)
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Call number:QA76.73.P98L877::2004 Show nearby items on shelf
Title:Learning Python
Author(s): Mark Lutz
David Ascher
Date:2004
Publisher:O'Reilly
Note:covers Python 2.3
ISBN:0596002815
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Call number:QA76.73.P98L36::2004 Show nearby items on shelf
Title:Python Scripting for Computational Science
Author(s): Hans Petter Langtangen
Date:2004
Publisher:Springer
ISBN:3540435085
Series:Texts in Computational Science and Engineering
Keywords: Python (Computer program language) , Science Data Processing
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Call number:QA76.73.P98L286::2009 Show nearby items on shelf
Title:A Primer on Scientific Programming with Python
Author(s): Hans Petter Langtangen
Date:2009
Publisher:Springer
ISBN:9783642024740
Series:Texts in Computational Science and Engineering v.6
Keywords: Python (Computer Program Language)
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Call number:QA76.73.P98K58::2010 Show nearby items on shelf
Title:Numerical methods in engineering with Python
Author(s): Jaan Kiusalaas
Date:2010
Edition:2nd ed
Publisher:Cambridge : Cambridge University Press
Size:422 p.
Contents:1. Introduction to Python -- 2. Systems of linear algebraic equations -- 3. Interpolation and curve fitting -- 4. Roots of equations -- 5. Numerical differentiation -- 6. Numerical integration -- 7. Initial value problems -- 8. Two-point boundary value problems -- 9. Symmetric Matrix Eigenvalue problems -- 10. Introduction to optimization -- Appendices
ISBN:9780521191326
Keywords: Python (Computer Program Language) , MATLAB , Engineering mathematics Data processing , Numerical analysis Data processing
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Call number:QA76.73.P98I3::2014 Show nearby items on shelf
Title:Python data analysis: learn how to apply powerful data analysis techniques with popular open source Python modules
Author(s): Ivan Idris
Date:2014
Publisher:Birmingham, UK: Packt Publishing Ltd
Size:329 p
Contents:Getting started with Python libraries -- NumPy arrays -- Statistics and linear algebra -- pandas primer -- Retrieving, processing, and storing data -- Data visualization -- Signal processing and time series -- Working with databases -- Analyzing tex tual data and social media -- Predictive analytics and machine learning -- Environments outside the Python ecosystem and cloud computing -- Performance tuning, profiling, and concurrency -- Appendix A : key concepts -- Appendix B : useful functions -- App endix C : online resources.
ISBN:9781783553358
Keywords: Python (Computer program language) , Programming languages (Electronic computers)
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Call number:QA76.73.P98H55::2015 Show nearby items on shelf
Title:Python for finance
Author(s): Yves J. Hilpisch
Date:2015
Edition:First edition.
Publisher:Sebastopol, CA: O'Reilly Media
Size:586 p
Contents:Part 1 Python and Finance, Part 2 Financial Analytics and Development, Part 3 Derivatives Analytics Library
ISBN:9781491945285
Keywords: Finance, Statistical methods, Data processing.
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Call number:QA76.73.P98H48::2017 Show nearby items on shelf
Title:Beginning Python : from novice to professional
Author(s): Magnus Lie Hetland
Date:2017
Edition:Third edition
Publisher:Apress
Size:527 p
Contents:Instant hacking: the basics -- Lists and tuples -- Working with strings -- Dictionaries: when indices won't do -- conditionals, loops, and some other statements -- Abstraction -- More abstraction -- Exceptions -- Magic methods, properties, and iterators -- batteries included -- Files and stuff -- Graphical user interfaces -- Database support -- Network programming -- Python and the web -- Testing, 1 2 3 -- Extending Python -- Packaging your programs -- Playful programming -- Project 1 Instant markup -- Project 2 Painting a pretty picture -- Project 3 XML for all occasions -- Project 4 In the news -- Project 5 A virtual tea party -- Project 6 Remote editing with CGI -- Project 7 Your own bulletin board -- Project 8 File sharing with XML-RPC -- Project 9 File sharing II No with GUI! -- Project 10 Do it yourself arcade game -- The short version -- Python reference
ISBN:9781484200292
Keywords: Computers , Pythong (Computer program language)
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Call number:QA76.73.P98H37::2000 Show nearby items on shelf
Title:The quick Python book
Author(s): Daryl D. Harms
Kenneth McDonald
Date:2000
Publisher:Manning, Greenwich, CT
Size:422
ISBN:1884777740
Keywords: Python (Computer program language)
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Call number:QA76.73.P98G78::2015 Show nearby items on shelf
Title:Data science from scratch: First principles with Python
Author(s): Joel Grus
Date:2015
Publisher:O'Reilly Media
Size:311 p.
Contents:Introduction -- A crash course in Python -- Visualizing data -- Linear algebra -- Statistics -- Probability -- Hypothesis and inference -- Gradient descent -- Getting data -- Working with data -- Machine learning -- k-Nearest neighbors -- Naive bayes -- Simple linear regression -- Multiple regression -- Logistic regression -- Decision trees -- Neural networks -- Clustering -- Natural language processing -- Network analysis -- Recommender systems -- Databases and SQL -- MapReduce -- Go forth and do dat a science.
ISBN:9781491901427
Keywords: Python (Computer program language) , Database management. , Data structures (Computer science)
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Call number:QA76.73.P98D69::2002 Show nearby items on shelf
Title:How To Think Like A Computer Scientist : Learning with Python
Author(s): Allen Downey
Jeffrey Elkner
Chris Meyers
Date:2009
Publisher:SoHo Books
ISBN:9781441419071
Keywords: Computer Programming , Python (Computer Programming)
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Call number:QA76.73.P98D397::2003 Show nearby items on shelf
Title:Python programming for the absolute beginner
Author(s): Michael Dawson
Date:2003
Publisher:Premier Press
Note:CD in back of book
ISBN:1592000738
Keywords: Python (Computer program language)
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Call number:QA76.73.P98C48::2007 Show nearby items on shelf
Title:Core Python programming
Author(s): Wesley Chun
Date:2007
Publisher:Prentice Hall, Upper Saddle River, NJ
Note:2nd ed.
ISBN:9780132269933
Series:Prentice Hall PTR core series
Keywords: Python (Computer program language)
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Call number:QA76.73.P98C32::2018 Show nearby items on shelf
Title:Deep learning with Python
Author(s): François Chollet
Date:2018
Publisher:Manning Publications Co.
Size:361 p
Contents:What is deep learning? -- Before we begin: the mathematical building blocks o fneural networks -- Getting started with neural networks -- Fundamentals of machine learning -- Deep learning for computer vision -- Deep learning for text and sequences -- Advanced deep-learning best practices -- Generative deep learning -- Conclusions
ISBN:9781617294433
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Call number:QA76.73.P98B57::2009 Show nearby items on shelf
Title:Natural language processing with Python
Author(s): Steven Bird
Ewan Klein
Edward Loper
Date:2009
ISBN:9780596516499
Keywords: Python (Computer program language) , Natural language processing (Computer science) , Sprachverarbeitung , Python <Programmiersprache>
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Call number:QA76.73.P98::2018 Show nearby items on shelf
Title:Python for data analysis : data wrangling with Pandas, NumPy, and IPython
Author(s): Wes McKinney
Date:2018
Edition:Second edition.
Publisher:Sebastopol, CA : O'Reilly Media
Size:524 p
ISBN:9781491957660
Keywords: Python (Computer program language) , Data mining.: TOC = Preliminaries -- Python language basics, IPython, and Jupyte
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Call number:QA76.73.P98.D54G73::2015 Show nearby items on shelf
Title:Two scoops of Django: best practices for Django 1.8
Author(s): Daniel Greenfeld
Audrey Roy
Date:2015
Publisher:Two Scoops Press
Size:495 p
ISBN:9780981467344
Keywords: Django (Electronic resource) , Python (Computer program language) , Web site development.
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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