GeoEngineerings

Michael E. Plesha, Gary L. Gray, Robert J. Witt, Francesco Costanzo ... 3557 pages - Language: ‎English - Publisher: McGraw-Hill Higher Education; 3rd edition (February, 2022).

Engineering Mechanics: Statics and Dynamics is the Problem Solver's Approach for Tomorrow's Engineers. Based upon a great deal of classroom teaching experience authors Plesha Gray andamp; Costanzo provide a rigorous introduction to the fundamental principles of statics and dynamics in a visually appealing framework for students.This title is available in Connect with SmartBook featuring Application-Based Activities the Free Body Diagram Tool and Process Oriented Problems. Instructor resources for this title include: an Image Library Lecture PPTs and an Instructor Solutions Manual.

Language: English - Level: Beginner - Number of Lessons: 78 - Duration: 5 hours and 26 minutes.

Statistics for Business Analytics: Data Analysis with Excel is a training course on the importance of statistics in business and business data analysis in Excel software, published by Udemy Academy. Statistical modeling is a very important skill for data analysts, and in this training course you will practice this skill with Excel software. Today, data has included all parts of our lives, and the success of business and various decisions in various industries depends on access to appropriate data and their correct analysis. The world is moving day by day towards a purely data-centric direction, and in this direction, many job positions have been created for data engineers and analysts.

This course is completely comprehensive and includes all the details of statistical modeling and business analysis. What you will learn?: Data Analysis with Excel:Basic principles and basics of statistics and their application in the world of business and various industries + Carrying out data analysis and analysis projects in the powerful Excel software environment + Various statistical methods and their exploitation to solve business problems and finalize data-driven decisions + Statistical assumption test with Excel software + Data-driven decision making and its principles + Business data analysis with descriptive statistics and statistical inference in Excel software + Construction and interpretation of various statistical models based on business data + Implementation of statistical analysis or regression analysis in Excel software to predict the future + Different techniques for analyzing huge and large data sets + Evaluation of different scenarios using available data ...

Language: English - Education Time: 7 hours and 28 minutes - Level: Elementary, Secondary - Size: 2.72 GB.

Data analysis is one of the leading jobs in the current technology market. As per the forecasts of Glassdoor and World Economic Forum, the demand for data scientists will also increase in the next few years. We are generating huge data every day from different domains like Social Media, Healthcare, Sensor data… we have a great tool to analyze them and the tool is R. R programming is a powerful language used widely for data analysis and statistical computing. It is completely free and has rich repositories for packages.

In this course first, you will learn how to install R and start programming on it. It will also help you to know the programming structures and functions. This R programming in Data Science and Data Analytics covers all the steps of Exploratory data analysis, Data pre-processing, and Modelling process. In EDA sections you will learn how to import data sets and create data frames from it. Then it will help you to visualize the variables using different plots. It will give you an initial structure of your data points. In Data pre-processing sections you will get the full idea of Missing value & outliers treatment and data split methods. Finally, you will be able to generate machine learning models using Linear and Logistic Regression.

This R programming for data science and data analytics is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!

Yuan Jiang ... 281 pages - Publisher: Artech House; (September, 2010) - Language: English - ISBN-10: 1608070883 - ISBN-13: 978-1608070886.

This practical resource provides engineers with a comprehensive understanding of error control coding, an essential and widely applied area in modern digital communications. The goal of error control coding is to encode information in such a way that even if the channel (or storage medium) introduces errors, the receiver can correct the errors and recover the original transmitted information. This book includes the most useful modern and classic codes, including block, Reed Solomon, convolutional, turbo, and LDPC codes. Professionals find clear guidance on code construction, decoding algorithms, and error correcting performances. Moreover, this unique book introduces computer simulations integrally to help readers master key concepts. Including a companion DVD with MATLAB programs and supported with over 540 equations, this hands-on reference provides an in-depth treatment of a wide range of practical implementation issues. DVD is included! It contains carefully designed MATLAB programs that practitioners can apply to their projects in the field.