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(8), April 2010 Those of us who have learned scientific programming in Python 'on the streets' could be a little jealous of students who;
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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The;
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libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix;
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libraries for data science and machine learning (pandas and sklearn), and a primer on Python classes and object-oriented programming. A new appendix;
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for ArcGIS and other fields such as remote sensing, GPS, spatial modeling, and statistical analysis. A Python Primer for ArcGIS® combines;
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of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis;
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Doing Science With Python introduces readers to the most popular coding tools for scientific research, such as Anaconda, Spyder, Jupyter;
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. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed;
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editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming;
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to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and;
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library. You'll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem;
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. Yoüll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later;
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A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book * The basics;
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that combines remarkable power with clear syntax. This book enables you to quickly create robust, reliable, and reusable Python applications by;
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and NumPy modules * A hands-on guide to implementing mathematics with Python, with complete coverage of all the key concepts Who This Book;
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focus of this book is on basic programming instructions used in machine learning and deep learning. Includes companion files with source code;
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Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python;
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Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python;
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, this book is for you. Even if you are not familiar with Python, Daniel Arbuckle's Mastering Python starts with the basics and takes you on a;
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Whether readers want to become a professional software developer, create web sites, analyze scientific data, or just automate tedious;
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Think like a programmer with this fun beginners guide to Python for ages 10 to 14 Kids can learn to code with;
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guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core;
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guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core;
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Python (R) is a free open-source language and environment that has tremendous potential in the scientific computing domain. Computing with;
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This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using;
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'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow;
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then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs. The;
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