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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: Abhinandan H. Patil
Publisher:
ISBN: 9781312613584
Category :
Languages : en
Pages : 0
Get Book Here
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: Aaron Maxwell
Publisher:
ISBN: 9780692878972
Category : Python (Computer program language)
Languages : en
Pages : 220
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Book Description
There are many books for those new to Python, new to programming, or both. Powerful Python is different. Written for experienced developers like you, its carefully crafted chapters teach intermediate and advanced strategies, patterns, and tools for modern Python. Focused on Python 3, with full support for 2.7. DRM-free digital upgrade: powerfulpython.com/book-upgrade "Feels like Neo learning Jiu jitsu in the Matrix." - John Beauford (@johnbeauford) "I just wanted to let you know what an excellent book this is... I keep going back to your book to learn Python." - Fahad Qazi, London, UK "Thanks. Keep up the good work. Your chapter on decorators is the best I have seen on that topic." - Leon Tietz, Minnesota, USA "Powerful Python is already helping me get huge optimization gains." - Timothy Dobbins (@TmthyDobbins) "What have I found good and valuable about the book so far? Everything honestly. The clear explanations, solid code examples have really helped me advance as a Python coder... Thank you! It has really helped me grasp some advanced concepts that I felt were beyond my abilities." - Nick S., Colorado, USA For data scientists, back-end engineers, web developers, sysadmins, devops, QA testers and more. What's included: An unrelenting selective spotlight on what's most valuable and impactful to working, full-time, professional Python developers Well-researched, detailed, realistic code on almost every page, powerfully illustrating key points. Very little "toy code" How to use decorators to add rich features to functions and classes; untangle distinct, frustratingly intertwined concerns in your code; and build powerful, extensible software frameworks How to use Python in ways that incentivize other developers to use and re-use your code, again and again... amplifying the impact of the code you write, and boosting your reputation among your peers Powerfully and easily weave iterators and generators throughout your applications, making them massively scalable, highly performant, and far more readable and maintainable How to fully leverage Python's exception and error model... giving you a detailed understanding even experienced Pythonistas often lack, and putting some of the most powerfully Pythonic exception-handling patterns in your toolbox How "magic methods" imbue natural, readable, expressive syntax into your classes and objects... and how to "break the rules" to craft stunningly intuitive, compellingly reusable library interfaces Valuable and powerful design patterns, and how Python's special language features give you uniquely powerful implementations not possible in other languages Deep and detailed instruction on how to write practical, realistic unit tests... using test-driven development to easily get into a state of flow... where you find yourself implementing feature after feature, keeping your focus with ease for long periods of time How to rapidly set up effective logging for scripts, sprawling Python applications, and everything in between An enthusiastic and unapologetic focus on Python 3, and what makes it great... with full explanation and support for getting the same results with Python 2.7 More at PowerfulPython.com.
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: 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: 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: John M. Stewart
Publisher: Cambridge University Press
ISBN: 1316641236
Category : Computers
Languages : en
Pages : 272
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Book Description
Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.
Author: Martin Jones
Publisher: Createspace Independent Publishing Platform
ISBN:
Category : Biology
Languages : en
Pages : 248
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Book Description
Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems.
Author: Dr. Krishna Kumar Mohbey
Publisher: BPB Publications
ISBN: 9391392067
Category : Computers
Languages : en
Pages : 468
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Book Description
step-by-step approach to Python programming with machine learning fundamental and theoretical principles. KEY FEATURES ● Introduces readers to Python programming in a very simple way. ● Extensive practical demonstration of Python concepts using numerous examples. ● Implementation of machine learning in Python using hands-on techniques. DESCRIPTION The book ‘Introduction to Python Programming: A Practical Approach’ lays out a path for readers who want to pursue a career in the field of computer software development. It covers the fundamentals of Python programming as well as machine learning principles. Students will benefit from the examples that are included with each concept, which will aid them in understanding the concept. This book provides a practical understanding of Python programming using numerous programs and examples. It also develops problem-solving and code-writing abilities for the readers. This book covers Python fundamentals, operators, and data structures such as strings, lists, dictionaries, and tuples. It also contains information on file and exception handling. The implementation of a machine learning model has also been included in this book. With the help of this book, students and programmers can improve their programming skills as well as their ability to sprint towards a rewarding career. WHAT YOU WILL LEARN ● Learn Python concepts, operators, and data structures. ● Learn the properties and operations of lists, tuples, and dictionaries. ● Write Python code to solve specific issues. ● Write Python code to handle disk files and exceptions. ● Work with OOPS properties like classes, objects, constructors, inheritance, and polymorphism. ● Use machine learning for classification, regression, prediction, and clustering. WHO THIS BOOK IS FOR This book is intended for current and aspiring emerging technology professionals, students, and anyone else who wishes to better understand the Python programming language and machine learning concepts. TABLE OF CONTENTS 1. Chapter 1: Basics of Python Programming 2. Chapter 2: Operators and Expressions 3. Chapter 3: Control Flow Statements 4. Chapter 4: Functions 5. Chapter 5: Strings 6. Chapter 6: Lists 7. Chapter 7: Tuple 8. Chapter 8: Dictionaries 9. Chapter 9: File Handling 10. Chapter 10: Exception Handling, Modules, and Packages 11. Chapter 11: Object-oriented Programming 12. Chapter 12: Machine Learning with Python 13. Chapter 13: Clustering with Python
Author: Alexander Lancaster
Publisher: Apress
ISBN: 9781484245224
Category : Computers
Languages : en
Pages : 376
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Book Description
Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. “A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective” -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow “Fun, entertaining, witty and darn useful. A magical portal to the big data revolution” -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School “Alex and Gordon’s enthusiasm for Python is contagious” -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley
Author: Joshua S. Weitz
Publisher: Princeton University Press
ISBN: 0691259615
Category : Science
Languages : en
Pages : 273
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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
