Python Coding One Year Later

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Python Coding One Year Later

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Author : R. L. Zimmerman
language : en
Publisher:
Release Date : 2021-02-09

Python Coding One Year Later written by R. L. Zimmerman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with categories.

The primary goal of this book is to learn the simple basics of debugging a Python script so your code runs as expected. Debugging is the process of finding and removing "bugs" or defects in a program, and it is also useful in getting your code to run in the first place! Chapter 3 presents "Python Basics" because a big part of debugging is knowing the correct syntax for a particular object and task. This book doesn't try to cover all the nuances of Python but does cover the terms and syntax you're likely to encounter in your first few weeks or months of programming. The overhead and clutter are gone, leaving behind clear and simple instructions. Code examples are self-contained, so you can copy and paste them into your IDE and run the program. There are certainly more elegant ways to do many of these tasks, but I wanted to demonstrate each concept with a working piece of code limited to a few lines. In Chapter 3, we'll look at the following topics and more. Functions, Lists, Dictionaries, Tuples, Ranges, Comprehension Indexing, Slicing, Comparison Operators, Control Statements There are dozens of diagrams that explain concepts such as indexing, slicing, scope, or recursive functions. We'll look at syntax relevant to each type of object. For example, to add to a "list," you could use 'append,' 'join' or 'extend' methods. While adding a new key:value pair to a dictionary is straightforward, adding to an existing dictionary can be confusing. The"type" of object in the key:value pair determines which methods you'll use to add, update, or delete objects. There are over 50 real-world code examples. Between the detailed Table of Contents and extensive Index, you can quickly find answers. The Index includes common phrases for those times when you don't know the technical term. For example, to find a string in Python, you could use the "in" comparison operator. Whether you look for "find" or "search," the Index refers you to the "in" comparison operator. The examples are varied so you can work with different types of data, such as: XML, HTML, matplotlib (plots/charts/graphs), OS (files/directories), *.txt, *.csv, user input, or dates.

Python Coding One Year Later

DOWNLOAD
Author : R. L. Zimmerman
language : en
Publisher:
Release Date : 2021-02-10

Python Coding One Year Later written by R. L. Zimmerman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-10 with categories.

The primary goal of this book is to learn the simple basics of debugging a Python script so your code runs as expected. Debugging is the process of finding and removing "bugs" or defects in a program, and it is also useful in getting your code to run in the first place! Chapter 3 presents "Python Basics" because a big part of debugging is knowing the correct syntax for a particular object and task. This book doesn't try to cover all the nuances of Python but does cover the terms and syntax you're likely to encounter in your first few weeks or months of programming. The overhead and clutter are gone, leaving behind clear and simple instructions. Code examples are self-contained, so you can copy and paste them into your IDE and run the program. There are certainly more elegant ways to do many of these tasks, but I wanted to demonstrate each concept with a working piece of code limited to a few lines. In Chapter 3, we'll look at the following topics and more. Functions, Lists, Dictionaries, Tuples, Ranges, Comprehension Indexing, Slicing, Comparison Operators, Control Statements There are dozens of diagrams that explain concepts such as indexing, slicing, scope, or recursive functions. We'll look at syntax relevant to each type of object. For example, to add to a "list," you could use 'append,' 'join' or 'extend' methods. While adding a new key:value pair to a dictionary is straightforward, adding to an existing dictionary can be confusing. The"type" of object in the key:value pair determines which methods you'll use to add, update, or delete objects. There are over 50 real-world code examples. Between the detailed Table of Contents and extensive Index, you can quickly find answers. The Index includes common phrases for those times when you don't know the technical term. For example, to find a string in Python, you could use the "in" comparison operator. Whether you look for "find" or "search," the Index refers you to the "in" comparison operator. The examples are varied so you can work with different types of data, such as: XML, HTML, matplotlib (plots/charts/graphs), OS (files/directories), *.txt, *.csv, user input, or dates.

Winning With Data Science

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Author : Howard Steven Friedman
language : en
Publisher: Columbia University Press
Release Date : 2024-01-30

Winning With Data Science written by Howard Steven Friedman and has been published by Columbia University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-30 with Computers categories.

Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams. Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrated through practical examples. The book follows the stories of Kamala and Steve, two professionals who need to collaborate with data science teams to achieve their business goals. Howard Steven Friedman and Akshay Swaminathan walk readers through each step of managing a data science project, from understanding the different roles on a data science team to identifying the right software. They equip readers with critical questions to ask data analysts, statisticians, data scientists, and other technical experts to avoid wasting time and money. Winning with Data Science is a must-read for anyone who works with data science teams or is interested in the practical side of the subject.

The Self Taught Computer Scientist

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Author : Cory Althoff
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-16

The Self Taught Computer Scientist written by Cory Althoff and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-16 with Computers categories.

The follow-up to Cory Althoff's bestselling The Self-Taught Programmer, which inspired hundreds of thousands of professionals to learn to program outside of school! Fresh out of college and with just a year of self-study behind him, Cory Althoff was offered a dream first job as a software engineer for a well-known tech company, but he quickly found himself overwhelmed by the amount of things he needed to know, but hadn’t learned yet. This experience combined with his personal journey learning to program inspired his widely praised guide, The Self-Taught Programmer. Now Cory's back with another guide for the self-taught community of learners focusing on the foundations of computer science. The Self-Taught Computer Scientist introduces beginner and self-taught programmers to computer science fundamentals that are essential for success in programming and software engineering fields. Computer science is a massive subject that could cover an entire lifetime of learning. This book does not aim to cover everything you would learn about if you went to school to get a computer science degree. Instead, Cory's goal is to give you an introduction to some of the most important concepts in computer science that apply to a programming career. With a focus on data structures and algorithms, The Self-Taught Computer Scientist helps you fill gaps in your knowledge, prepare for a technical interview, feel knowledgeable and confident on the job, and ultimately, become a better programmer. Learn different algorithms including linear and binary search and test your knowledge with feedback loops Understand what a data structure is and study arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs Prepare for technical interviews and feel comfortable working with more experienced colleagues Discover additional resources and tools to expand your skillset and continue your learning journey It's as simple as this: You have to study computer science if you want to become a successful programmer, and if you don't understand computer science, you won't get hired. Ready for a career in programming, coding, or software engineering and willing to embrace an "always be learning" mindset? The Self-Taught Computer Scientist is for you.

Machine Learning Using Python

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Author : Dr. Ramu Kuchipudi, Dr. K. Sai Madhuri, Dr. Vivek Ravishankar Dubey, Dr. Ashish B. Patel
language : en
Publisher: BR Publications
Release Date : 2025-12-09

Machine Learning Using Python written by Dr. Ramu Kuchipudi, Dr. K. Sai Madhuri, Dr. Vivek Ravishankar Dubey, Dr. Ashish B. Patel and has been published by BR Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-09 with Computers categories.

Machine Learning using Python introduces the concepts, techniques, and applications of machine learning with practical implementation using the Python programming language. The course focuses on data preprocessing, exploratory data analysis, and the use of supervised and unsupervised learning algorithms such as linear regression, classification, clustering, and decision trees. It covers popular Python libraries including NumPy, Pandas, Matplotlib, and Scikit-learn for building, training, and evaluating models. This subject equips learners with hands-on skills to develop intelligent data-driven solutions for real-world problems in domains such as business analytics, healthcare, and engineering.

Evolutionary Machine Learning Techniques

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Author : Seyedali Mirjalili
language : en
Publisher: Springer Nature
Release Date : 2019-11-11

Evolutionary Machine Learning Techniques written by Seyedali Mirjalili and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Technology & Engineering categories.

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.

Professional Ironpython

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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2010-04-27

Professional Ironpython written by John Paul Mueller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-27 with Computers categories.

Thorough coverage of Microsoft’s new dynamic programming language: IronPython IronPython is a powerful and vital part of any .NET developer's toolbox, and although it is several years old, very little literature exists on the topic. This essential resource fills that void and provides you with an in-depth understanding of IronPython. A brief introduction walks you through the installation, usage, and tools of IronPython and also explains what makes IronPython different from other programming languages. Coverage quickly moves on to explaining how to use and work with the IronPython language, and an in-depth look at its environment sheds light on how it can be stand alone or with the .NET Framework. You'll see how IronPython can be used to create either desktop or Web-based applications and you’ll witness how it interacts with other existing technologies. In addition, coverage of advanced topics shares techniques for extending IronPython and making it a robust language. Provides you with an in-depth look at IronPython, how it is different from other programming languages, what it is capable of, and how to maximize its potential Explores how IronPython interacts with existing technologies and how it can perform administration tasks Answers popular questions, such as how to extend IronPython and make it a more robust language Tackles topics not addressed anywhere else, including executing IronPython using Mono You'll want to devour every topic covered in Professional IronPython so you can get started working with this powerful programming language today.

Learning Functional Programming

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Author : Jack Widman
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-08-11

Learning Functional Programming written by Jack Widman 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 2022-08-11 with Computers categories.

Learn how to think and write code like a functional programmer. With this practical guide, software developers familiar with object-oriented programming will dive into the core concepts of functional programming and learn how to use both functional and OOP features together on large or complex software projects. Author Jack Widman uses samples from Java, Python, C#, Scala, and JavaScript to help you gain a new perspective and a set of tools for managing the complexity in your problem domain. You'll be able to write code that's simpler, reusable, easier to test and modify, and more consistently correct. This book also shows you how to use patterns from category theory to help bridge the gap between OOP and functional programming. Learn functional programming fundamentals and explore the way functional programmers approach problems Understand how FP differs from object-oriented and imperative programming Use a set of practical, applicable design patterns that model reality in a functional way Learn how to incorporate FP and OOP features into software projects Apply functional design patterns appropriately and use them to write correct, robust, and easily modifiable code

Analytical Groundwater Modeling

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Author : Mark Bakker
language : en
Publisher: CRC Press
Release Date : 2022-06-30

Analytical Groundwater Modeling written by Mark Bakker and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Mathematics categories.

This book provides a detailed description of how Python can be used to give insight into the flow of groundwater based on analytic solutions. Starting with simple problems to illustrate the basic principles, complexity is added step by step to show how one-dimensional and two-dimensional models of one or two aquifers can be implemented. Steady and transient flow problems are discussed in confined, semi-confined, and unconfined aquifers that may include wells, rivers, and areal recharge. Special consideration is given to coastal aquifers, including the effect of tides and the simulation of interface flow. Application of Python allows for compact and readable code, and quick visualization of the solutions. Python scripts are provided to reproduce all results. The scripts are also available online so that they can be altered to meet site-specific conditions. This book is intended both as training material for the next generation of university students and as a useful resource for practitioners. A primer is included for those who are new to Python or as a refresher for existing users.

The Internet Encyclopedia Volume 1 A F

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Author :
language : en
Publisher: John Wiley & Sons
Release Date : 2004-11-11

The Internet Encyclopedia Volume 1 A F written by and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11-11 with Business & Economics categories.

The Internet Encyclopedia in a 3-volume reference work on the internet as a business tool, IT platform, and communications and commerce medium.