Author: Aquiles Carattino
Publisher:
ISBN: 9781716517686
Category :
Languages : en
Pages : 190
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Book Description
Python for the Lab is the first book covering how to develop instrumentation software. It is ideal for researchers willing to automatize their setups and bring their experiments to the next level. The book is the product of countless workshops at different universities, and a carefully design pedagogical strategy. With an easy to follow and task-oriented design, the book uncovers all the best practices in the field. It also shows how to design code for long-term maintainability, opening the doors of fruitful collaboration among researchers from different labs.
Author: Joshua S. Weitz
Publisher: Princeton University Press
ISBN: 0691255679
Category : Computers
Languages : en
Pages : 272
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Book Description
A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students—whether from the life sciences, physics, computational sciences, engineering, or mathematics—how to reason quantitatively in the face of uncertainty. Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communities Encourages good coding practices, clear and understandable modeling, and accessible presentation of results Helps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scale Builds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulations Bridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their own Stand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB
Author: Kevin Wilson
Publisher: Elluminet Press
ISBN: 1738452573
Category : Computers
Languages : en
Pages : 293
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Book Description
Python Made Easy: A First Course in Computer Programming is a full color, step by step, hands-on introduction to the world of computer programming using Python. With a focus on practical application, this book is designed to equip anyone seeking an interactive introduction to Python with the essential skills and knowledge needed to start their programming journey. This book adopts a "learn by doing" approach, providing a rich set of lab exercises at the end of each section and larger programming projects for you to try. By actively engaging with coding exercises along with step-by-step guidance, illustrations, and video demos, you'll develop a solid understanding of Python and build your skills. Here's what you'll learn Install Python on Windows, Mac, and Linux Python syntax and basics Data types and Data structures File Handling Python Functions Exception and Error Handling in Python Object Oriented Programming Using Modules and Libraries in your Python Programs Building GUIs and using Graphics Turtle Graphics Game Development Testing and Debugging your Programs How to deploy your Python Programs Web Development using Python Frameworks Python Made Easy: A First Course in Computer Programming using Python is the ideal companion for anyone seeking an interactive introduction to Python programming. Whether you are a student, an aspiring programmer, or a professional from a non-technical background, this book will empower you to master the fundamentals of Python and the world of computer programming. Have Fun!
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 743
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author: Philipp Kats
Publisher: Packt Publishing Ltd
ISBN: 1789533066
Category : Computers
Languages : en
Pages : 464
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Book Description
Understand the constructs of the Python programming language and use them to build data science projects Key FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Z Fetcher
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 132
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Book Description
The book is meant and designed mainly for those learner who have programming background and want to learn Python for their benefits.
Author: Abhinandan H. Patil
Publisher:
ISBN: 9781312613584
Category :
Languages : en
Pages : 0
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Book Description
This book is totally informal and unconventional in its approach. Theory text is kept bare minimal. Targeted readers of this book are novice Python programmers. Author mentions about some Authoritative books by other competent Authors for beginners. The Author takes problem and solution approach . This book contains close to 20 practical problems and their solutions for beginners. The Author strongly asserts his copyright over content in this book that he prepared for teaching. This book is lab oriented and tests you on your learned concepts. After solving all the problems you should have gained some knowledge in Python. The intention of these book is to help novice learner. Good luck!.
Author: Kevin Wilson
Publisher: Illustrated Coding
ISBN: 9781913151782
Category :
Languages : en
Pages : 0
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Book Description
Written as an illustrated, step-by-step guide and workbook, this full color book will introduce you to Python using clear explanations, diagrams, examples, lab exercises and video demos.
Author: Al Sweigart
Publisher: No Starch Press
ISBN: 1718501250
Category : Computers
Languages : en
Pages : 433
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Book Description
Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity. If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online. You’ll create: • Hangman, Blackjack, and other games to play against your friends or the computer • Simulations of a forest fire, a million dice rolls, and a Japanese abacus • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver • A first-person 3D maze game • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
