Plot graphs, solve equations, and write code in a flash! If you work in a STEM field, chances are you'll be using MATLAB on a daily basis. MATLAB is a popular and powerful computational tool and this book provides everything you need to start manipulating and plotting your data. MATLAB has rapidly become the premier data tool, and MATLAB For Dummies is a comprehensive guide to the fundamentals. MATLAB For Dummies guides you through this complex computational language from installation to visualization to automation. Learn MATLAB's language fundamentals including syntax, operators, and data types Understand how to use the most important window in MATLAB – the Command Window Get the basics of linear algebra to get up and running with vectors, matrices, and hyperspace Automate your work with programming scripts and functions Plot graphs in 2D and 3D to visualize your data Includes a handy guide for MATLAB's functions and plotting routines MATLAB is an essential part of the analysis arsenal and MATLAB For Dummies provides clear, thorough guidance to get the most out of your data.
Unleash the power of Python for your data analysis projectswith For Dummies! Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to take advantage ofPython programming to acquire, organize, process, and analyze largeamounts of information and use basic statistics concepts toidentify trends and patterns. You’ll get familiar with thePython development environment, manipulate data, design compellingvisualizations, and solve scientific computing challenges as youwork your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming andstatistics to help you build a solid foundation in data scienceconcepts like probability, random distributions, hypothesistesting, and regression models Explains objects, functions, modules, and libraries and theirrole in data analysis Walks you through some of the most widely-used libraries,including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python,Python for Data Science For Dummies is your practical guideto getting a grip on data overload and doing interesting thingswith the oodles of information you uncover.
A Practical Introduction to Programming and Problem Solving (MATLAB for Engineers, MATLAB for Scientists, MATLAB Programming for Dummies)
Author: Learning, Upskill
Learn MATLAB Programming in Less Than 24 Hours!MATLAB - A Practical Introduction to Programming and Problem Solving is exclusively designed for MATLAB Beginners. Programming with MATLAB is a step-by-step comprehensive guide that equips your skills in MATLAB. Whether you are a Math Student, Researcher, Teacher, Engineer or Scientist - this book covers the in-and-out of the essentials you need to learn to become familiar with MATLAB. What You'll Learn From This Book?Introduction To MATLABChapter 1: MATLAB - Intro, Features, Modules & InfluenceChapter 2: Getting started with MATLABChapter 3: Getting familiar with MATLABChapter 4: Basic Commands in MATLABChapter 5: Matrix OperationsChapter 6: Array and Linear OperationsChapter 7: Programming with MATLABChapter 8: Input, Output and OperatorsChapter 9: Flow Control StatementsChapter 10: Math FunctionsChapter 11: StringsChapter 12: PlotsChapter 13: Graphics and Graphical User Interface ProgrammingChapter 14: Autocorrelation using MATLABChapter 15: How To Become A MATLAB Expert?MATLAB has influence over many areas of human technology from Artificial Intelligence to Aerospace. Mastering the basics of MATLAB gives you the ability to learn advanced topics more easily, create amazing tools and software, and conduct engineering tasks with ease. If you want to learn MATLAB for your Work or College, this is the right book for you.
Loaded with the latest Photoshop tips and techniques The secrets of digital image editing - explained in plain English! Photoshop CS3 is a powerhouse, and here's the fast and easy way to get up to speed on all the coolest features. This friendly guide helps you get images into Photoshop - and then turn them into dazzling works of art. You'll see how to work in the right file formats, master the Brushes palette, get creative with filters, convert color to grayscale, and more! Adjust brightness, improve color, and fix flaws Take advantage of the Raw file format Composite images with layers and blending modes Automate your tasks with scripts and Actions Apply the new Smart Filters to Smart Objects
For problems that require extensive computation, a C++ program can race through billions of examples faster than most other computing choices. C++ enables mathematicians of virtually any discipline to create programs to meet their needs quickly, and is available on most computer systems at no cost. C++ for Mathematicians: An Introduction for Students and Professionals accentuates C++ concepts that are most valuable for pure and applied mathematical research. This is the first book available on C++ programming that is written specifically for a mathematical audience; it omits the language’s more obscure features in favor of the aspects of greatest utility for mathematical work. The author explains how to use C++ to formulate conjectures, create images and diagrams, verify proofs, build mathematical structures, and explore myriad examples. Emphasizing the essential role of practice as part of the learning process, the book is ideally designed for undergraduate coursework as well as self-study. Each chapter provides many problems and solutions which complement the text and enable you to learn quickly how to apply them to your own problems. An accompanying CD ROM provides all numbered programs so that readers can easily use or adapt the code as needed. Presenting clear explanations and examples from the world of mathematics that develop concepts from the ground up, C++ for Mathematicians can be used again and again as a resource for applying C++ to problems that range from the basic to the complex.
للفيزياء الحرارية أهمية كبيرة في فهم العالم الذي نعيش فيه، إذ إن لكل جسم من حولنا هويته الحرارية الخاصة به التي تمنحه خواص فيزيائية مختلفة. إن كتاب (الفيزياء الحرارية) وضع ليوضح علاقة حرارة المواد بما حولها، ويجيب عن كثير من الأسئلة التي يمكن أن تخطر ببالنا. وينقسم كتاب (الفيزياء الحرارية) إلى أربعة أقسام رئيسة، حيث يناقش القسم الأول الأساسيات من مثل القانونين الأول والثاني، والطاقة في الفيزياء الحرارية والتفاعلات والدلالات كالبارامغناطيسية والاتزان الميكانيكي والضغط واتزان وانتشار الجهد الميكانيكي، ويتمحور القسم الثاني حول الثرموديناميكا، والمكائن الحرارية والثلاجات ومكائن الاحتراق الداخلي والماكينة البخارية والطاقة الحرة وتحولاتها. القسم الثالث والأخير من الكتاب يتناول ميكانيكا الإحصاء، كإحصاء بولتزمان والإحصاء الكمّي، وأنظمة الجسيمات المتفاعلة. ويختتم الكتاب بملحقين: الأول عن عناصر ميكانيكا الكمّ والثاني عن النتائج الرياضية. الكتاب يحتوي على تطبيقات في مجالات متعددة، كالكيمياء والجيولوجيا وعلوم الحياة وعلوم البيئة وعلم التعدين وفيزياء الجوامد وفيزياء الفلك، وغيرها مما يساعد على استيعاب أكبر لمفاهيم الفيزياء الحرارية وأسسها. العبيكان للنشر
This work assesses empirically the various explanations for why productivity growth is procyclical. Some theories of business cycles state that productivity movements reflect changes in technology and are the driving force of economic fluctuations. This study investigates whether price-cost margins, externalities, or slow adjustment of the labor market can account for the behavior of productivity growth over the cycle. The application of standard econometric techniques to two different measures of productivity growth in American manufacturing industries, one based on quantities and one based on prices, shows that there is some labor hoarding, which is compatible with either margins or externalities.
Core Concepts in Data Analysis: Summarization, Correlation and Visualization provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate different aspects of data (decision trees, linear rules, neuron networks, and Bayes rule). Boris Mirkin takes an unconventional approach and introduces the concept of multivariate data summarization as a counterpart to conventional machine learning prediction schemes, utilizing techniques from statistics, data analysis, data mining, machine learning, computational intelligence, and information retrieval. Innovations following from his in-depth analysis of the models underlying summarization techniques are introduced, and applied to challenging issues such as the number of clusters, mixed scale data standardization, interpretation of the solutions, as well as relations between seemingly unrelated concepts: goodness-of-fit functions for classification trees and data standardization, spectral clustering and additive clustering, correlation and visualization of contingency data. The mathematical detail is encapsulated in the so-called “formulation” parts, whereas most material is delivered through “presentation” parts that explain the methods by applying them to small real-world data sets; concise “computation” parts inform of the algorithmic and coding issues. Four layers of active learning and self-study exercises are provided: worked examples, case studies, projects and questions.