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Appunti Di Programmazione Scientifica In Python


Appunti Di Programmazione Scientifica In Python
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Appunti Di Programmazione Scientifica In Python


Appunti Di Programmazione Scientifica In Python
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Author : Fabio Aiolli
language : it
Publisher: Società Editrice Esculapio
Release Date : 2020-05-01

Appunti Di Programmazione Scientifica In Python written by Fabio Aiolli and has been published by Società Editrice Esculapio this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-01 with Computers categories.


Saper programmare un computer è una capacità oramai necessaria a chiunque voglia addentrarsi nello studio delle scienze. Da questo punto di vista, il linguaggio Python sta diventando sempre più popolare per la programmazione in ambito scientifico. Python è un linguaggio di alto livello che usa il paradigma della programmazione orientata agli oggetti (OOP). È un linguaggio semplice e, a differenza di altri linguaggi di programmazione, non richiede l’apprendimento di tecnicismi che spesso distolgono dal vero scopo: imparare a programmare! Questo libro propone una guida completa alla programmazione, fornendo i principi fondamentali utili ad esprimere con un algoritmo la soluzione ad un problema specifico. Nel libro sono schematizzate le problematiche ricorrenti della programmazione e per queste vengono presentati esempi e soluzioni corrette, efficienti ed eleganti. Il volume approfondisce i fondamentali della programmazione: la selezione e la iterazione, la ricorsione, le strutture dati complesse quali liste concatenate ed alberi e gli algoritmi di ricerca, ordinamento e il backtracking. I concetti teorici presentati vengono poi ampiamente applicati a problemi scientifici reali e ai giochi.



Python 3 Image Processing


Python 3 Image Processing
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Author : Pajankar Ashwin
language : en
Publisher: BPB Publications
Release Date : 2019-09-20

Python 3 Image Processing written by Pajankar Ashwin and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.


Gain a working knowledge of practical image processing and with scikit-image.Key features Comprehensive coverage of various aspects of scientific Python and concepts in image processing. Covers various additional topics such as Raspberry Pi, conda package manager, and Anaconda distribution of Python. Simple language, crystal clear approach, and straight forward comprehensible presentation of concepts followed by code examples and output screenshots. Adopting user-friendly style for explanation of code examples.DescriptionThe book has been written in such a way that the concepts are explained in detail, giving adequate emphasis on code examples. To make the topics more comprehensive, screenshots and code samples are furnished extensively throughout the book. The book is conceptualized and written in such a way that the beginner readers will find it very easy to understand the concepts and implement the programs.The book also features the most current version of Raspberry Pi and associated software with it. This book teaches novice beginners how to write interesting image processing programs with scientific Python ecosystem. The book will also be helpful to experienced professionals to make transition to rewarding careers in scientific Python and computer vision. What will you learn Raspberry Pi, Python 3 Basics Scientific Python Ecosystem NumPy and Matplotlib Visualization with Matplotlib Basic NumPy, Advanced Image Processing with NumPy and Matplotlib Getting started with scikit-image Thresholding, Histogram Equalization, and Transformations Kernels, Convolution, and Filters Morphological Operations and Image Restoration Noise Removal and Edge Detection Advanced Image Processing OperationsWho this book is for Students pursuing BE/BSc/ME/MSc/BTech/MTech in Computer Science, Electronics, Electrical, and Mathematics Python enthusiasts Computer Vision and Image Processing professionals Anyone fond of tinkering with Raspberry Pi Researchers in Computer Vision Table of contents1. Concepts in Image Processing2. Installing Python 3 on Windows3. Introduction to Raspberry Pi4. Python 3 Basics5. Introduction to the Scientific Python Ecosystem6. Introduction to NumPy and Matplotlib7. Visualization with Matplotlib8. Basic Image Processing with NumPy and Matplotlib9. Advanced Image Processing with NumPy and Matplotlib10. Getting Started with Scikit-Image11. Thresholding Histogram Equalization and Transformations12. Kernels, Convolution and Filters13. Morphological Operations and Image Restoration14. Noise Removal and Edge Detection15. Advanced Image Processing Operations16. Wrapping UpAbout the authorAshwin Pajankar is a polymath. He has more than two decades of programming experience. He is a Science Popularizer, a Programmer, a Maker, an Author, and a Youtuber. He is passionate about STEM (Science-Technology-Education-Mathematics) education. He is also a freelance software developer and technology trainer. He graduated from IIIT Hyderabad with M.Tech. in Computer Science and Engineering. He has worked in a few multinational corporations including Cisco Systems and Cognizant for more than a decade. Ashwin is also an online trainer with various eLearning platforms like BPBOnline, Udemy, and Skillshare. In his free time, he consults on the topics of Python programming and data science to the local software companies in the city of Nasik. He is actively involved in various social initiatives and has won many accolades during his student life and at his past workplaces.His Website: http://www.ashwinpajankar.com/His LinkedIn Profile: https://www.linkedin.com/in/ashwinpajankar/



Python Graphics


Python Graphics
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Author : B.J. Korites
language : en
Publisher: Apress
Release Date : 2018-06-20

Python Graphics written by B.J. Korites and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-20 with Computers categories.


Use Python's built-in features to create innovative graphics for data visualization and technical illustrations. This book goes beyond simple commands and libraries to explain how to not only display but also rotate, shade, and edit graphics for any purpose. Starting with the essential Python functions to set up a plotting space and produce 2 and 3-dimensional objects, you'll learn how to construct more complex objects, translate and rotate them, remove hidden lines, introduce shading to add realism, and project images to visualize any dataset. The final chapter includes several worked applications in science and engineering including planetary models, which you can adapt for your own use. Written for developers who want to harness Python's capabilities to fine-tune their images, Python Graphics covers the different commands for plotting dots, lines, arrows, or arcs, creating custom plotting grids, correcting distortions, adding text and labels to illustrations, manipulating arcs and circles, specify and use colors, and more. Armed with these techniques and core math skills, you'll be ready to create and customize detailed technical illustrations or data visualizations. What You'll Learn Use Python′s built-in commands for plotting, removing distortions, and rotating objects Create and edit 2D and 3D objects Develop illustrations for scientific and engineering applications Who This Book Is For Python developers looking for tips on how to create illustrations and visualizations, as well as scientists, engineers, or students using Python. It assumes familiarity with vectors, matrices, geometry and trigonometry.



Data Science Projects With Python


Data Science Projects With Python
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Author : Stephen Klosterman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-29

Data Science Projects With Python written by Stephen Klosterman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-29 with Computers categories.


Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost Key FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate data-driven insights with confidence and clarityBook Description If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable. In this book, you'll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you'll experience in real-world data science projects. You'll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world. By the end of this data science book, you'll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data. What you will learnLoad, explore, and process data using the pandas Python packageUse Matplotlib to create compelling data visualizationsImplement predictive machine learning models with scikit-learnUse lasso and ridge regression to reduce model overfittingEvaluate random forest and logistic regression model performanceDeliver business insights by presenting clear, convincing conclusionsWho this book is for Data Science Projects with Python – Second Edition is for anyone who wants to get started with data science and machine learning. If you're keen to advance your career by using data analysis and predictive modeling to generate business insights, then this book is the perfect place to begin. To quickly grasp the concepts covered, it is recommended that you have basic experience of programming with Python or another similar language, and a general interest in statistics.



Deep Learning With Tensorflow 2 And Keras


Deep Learning With Tensorflow 2 And Keras
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Author : Antonio Gulli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-12-27

Deep Learning With Tensorflow 2 And Keras written by Antonio Gulli and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-27 with Computers categories.


Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected.



Cython


Cython
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Author : Kurt W. Smith
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-01-21

Cython written by Kurt W. Smith and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-21 with Computers categories.


Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP



Advanced Python Programming


Advanced Python Programming
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Author : Dr. Gabriele Lanaro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-02-28

Advanced Python Programming written by Dr. Gabriele Lanaro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Computers categories.


Create distributed applications with clever design patterns to solve complex problems Key FeaturesSet up and run distributed algorithms on a cluster using Dask and PySparkMaster skills to accurately implement concurrency in your codeGain practical experience of Python design patterns with real-world examplesBook Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: Python High Performance - Second Edition by Gabriele LanaroMastering Concurrency in Python by Quan NguyenMastering Python Design Patterns by Sakis KasampalisWhat you will learnUse NumPy and pandas to import and manipulate datasetsAchieve native performance with Cython and NumbaWrite asynchronous code using asyncio and RxPyDesign highly scalable programs with application scaffoldingExplore abstract methods to maintain data consistencyClone objects using the prototype patternUse the adapter pattern to make incompatible interfaces compatibleEmploy the strategy pattern to dynamically choose an algorithmWho this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.



Guide To Competitive Programming


Guide To Competitive Programming
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Author : Antti Laaksonen
language : en
Publisher: Springer
Release Date : 2018-01-02

Guide To Competitive Programming written by Antti Laaksonen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-02 with Computers categories.


This invaluable textbook presents a comprehensive introduction to modern competitive programming. The text highlights how competitive programming has proven to be an excellent way to learn algorithms, by encouraging the design of algorithms that actually work, stimulating the improvement of programming and debugging skills, and reinforcing the type of thinking required to solve problems in a competitive setting. The book contains many “folklore” algorithm design tricks that are known by experienced competitive programmers, yet which have previously only been formally discussed in online forums and blog posts. Topics and features: reviews the features of the C++ programming language, and describes how to create efficient algorithms that can quickly process large data sets; discusses sorting algorithms and binary search, and examines a selection of data structures of the C++ standard library; introduces the algorithm design technique of dynamic programming, and investigates elementary graph algorithms; covers such advanced algorithm design topics as bit-parallelism and amortized analysis, and presents a focus on efficiently processing array range queries; surveys specialized algorithms for trees, and discusses the mathematical topics that are relevant in competitive programming; examines advanced graph techniques, geometric algorithms, and string techniques; describes a selection of more advanced topics, including square root algorithms and dynamic programming optimization. This easy-to-follow guide is an ideal reference for all students wishing to learn algorithms, and practice for programming contests. Knowledge of the basics of programming is assumed, but previous background in algorithm design or programming contests is not necessary. Due to the broad range of topics covered at various levels of difficulty, this book is suitable for both beginners and more experienced readers.



Extreme C


Extreme C
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Author : Kamran Amini
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-10-31

Extreme C written by Kamran Amini and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.


Push the limits of what C - and you - can do, with this high-intensity guide to the most advanced capabilities of C Key FeaturesMake the most of C’s low-level control, flexibility, and high performanceA comprehensive guide to C’s most powerful and challenging featuresA thought-provoking guide packed with hands-on exercises and examplesBook Description There’s a lot more to C than knowing the language syntax. The industry looks for developers with a rigorous, scientific understanding of the principles and practices. Extreme C will teach you to use C’s advanced low-level power to write effective, efficient systems. This intensive, practical guide will help you become an expert C programmer. Building on your existing C knowledge, you will master preprocessor directives, macros, conditional compilation, pointers, and much more. You will gain new insight into algorithm design, functions, and structures. You will discover how C helps you squeeze maximum performance out of critical, resource-constrained applications. C still plays a critical role in 21st-century programming, remaining the core language for precision engineering, aviations, space research, and more. This book shows how C works with Unix, how to implement OO principles in C, and fully covers multi-processing. In Extreme C, Amini encourages you to think, question, apply, and experiment for yourself. The book is essential for anybody who wants to take their C to the next level. What you will learnBuild advanced C knowledge on strong foundations, rooted in first principlesUnderstand memory structures and compilation pipeline and how they work, and how to make most out of themApply object-oriented design principles to your procedural C codeWrite low-level code that’s close to the hardware and squeezes maximum performance out of a computer systemMaster concurrency, multithreading, multi-processing, and integration with other languagesUnit Testing and debugging, build systems, and inter-process communication for C programmingWho this book is for Extreme C is for C programmers who want to dig deep into the language and its capabilities. It will help you make the most of the low-level control C gives you.



Avr Programming


Avr Programming
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Author : Elliot Williams
language : en
Publisher: Maker Media, Inc.
Release Date : 2014-01-27

Avr Programming written by Elliot Williams and has been published by Maker Media, Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-27 with Computers categories.


Atmel's AVR microcontrollers are the chips that power Arduino, and are the go-to chip for many hobbyist and hardware hacking projects. In this book you'll set aside the layers of abstraction provided by the Arduino environment and learn how to program AVR microcontrollers directly. In doing so, you'll get closer to the chip and you'll be able to squeeze more power and features out of it. Each chapter of this book is centered around projects that incorporate that particular microcontroller topic. Each project includes schematics, code, and illustrations of a working project. Program a range of AVR chips Extend and re-use other people’s code and circuits Interface with USB, I2C, and SPI peripheral devices Learn to access the full range of power and speed of the microcontroller Build projects including Cylon Eyes, a Square-Wave Organ, an AM Radio, a Passive Light-Sensor Alarm, Temperature Logger, and more Understand what's happening behind the scenes even when using the Arduino IDE