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Simpson A: Python Automation For Dummies

Python Automation For Dummies

Modern Computational Approaches to Hijri Calendar, Qibla, and Prayer Times

Python for Islamic Astronomy

Learning to code has never been easier than with this innovative visual guide to computer programming for beginners. In our digital world, coding skills are in high demand and the need for programmers is still growing. Taking the first steps in learning to code may seem daunting, but by using a graphic method to break code into small chunks, this book brings essential skills easily within reach. Each chapter explores one of the most popular languages, with practical programming projects to show you how programming works. You'll learn to think like a programmer by breaking a problem down into parts before turning those parts into lines of code. Short, easy-to-follow steps then show you, piece by piece, how to build a complete program. There are challenges for you to tackle to build your confidence before moving on. Written by a team of expert coders and coding teachers, the Beginner's Step-by-Step Coding Course is the ideal way to understand coding.

Learn Computer Programming the Easy Way

Beginner's Step-by-Step Coding Course

Learn How to Code through Interactive Examples

Python Practice Lab

This book illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, the book is written for students and professionals. It is focused on learning outcomes and problem solving.

Demystifying Probability and Statistics for Data Scientists with R

The Linux Memory Manager

Machine Learning For Dummies

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Learn dozens of tried-and-true strategies to find and fix coding mistakes with this efficient debugging guide that slashes the time required for this tedious task. Most programmers dread debugging, but it remains a critical skill and one often learned through trial and error. This book offers a shortcut, distilling the experience of top-tier game designer Johannes Kuhlmann – who has worked on popular games like Valheim and Saints Row – into clear, practical strategies for debugging complex software in record time. This book offers more than 25 reliable strategies to tackle bugs at every level of development, helping to ensure that quality products go to market on schedule. Each chapter blends technical advice with instructive examples from the author’s own career, offering widely applicable, language-agnostic techniques from which both novice programmers and seasoned developers will benefit. The Debugging Handbook is not just a manual to reach for time and again but a mentor, helping programmers develop the mindset to quickly squash any bug.

The Debugging Handbook

Foundations, Technologies, and Prospects for the Future

Autonomous Vehicle Safety Solutions

A one-stop-shop for all the math you should have learned for your programming career. Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.&nbsp; In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms. Through clear explanations and practical examples, you’ll learn to: <ul><li>Harness linear algebra to manipulate data with unprecedented efficiency</li><li>Apply calculus concepts to optimize algorithms and drive simulations</li><li>Use probability and statistics to model uncertainty and analyze data</li><li>Master the discrete mathematics that powers&nbsp;modern data structures</li><li>Solve dynamic problems through differential equations</li></ul> Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.

Math for Programming

Gender, Race and the Power of Code in a Galaxy Far, Far Away

Decoding Star Wars

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools-just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

Python Automation For Dummies

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