Machine Component Analysis with MATLAB

• Author : Dan B. Marghitu,Mihai Dupac
• Publisher : Butterworth-Heinemann
• Release : 15 March 2019

Machine Design Analysis with MATLAB is a highly practical guide to the fundamental principles of machine design which covers the static and dynamic behavior of engineering structures and components. MATLAB has transformed the way calculations are made for engineering problems by computationally generating analytical calculations, as well as providing numerical calculations. Using step-by-step, real world example problems, this book demonstrates how you can use symbolic and numerical MATLAB as a tool to solve problems in machine design. This book provides

• Author : Atif Iqbal,Shaikh Moinoddin,B. Prathap Reddy
• Publisher : John Wiley & Sons
• Release : 08 June 2021

A comprehensive text, combining all important concepts and topics of Electrical Machines and featuring exhaustive simulation models based on MATLAB/Simulink Electrical Machine Fundamentals with Numerical Simulation using MATLAB/Simulink provides readers with a basic understanding of all key concepts related to electrical machines (including working principles, equivalent circuit, and analysis). It elaborates the fundamentals and offers numerical problems for students to work through. Uniquely, this text includes simulation models of every type of machine described in the book, enabling

• Author : G. Peck
• Publisher : Createspace Independent Publishing Platform
• Release : 31 October 2017

Statistics and Machine Learning Toolbox provides functions and apps to describe, analyze, and model data. You can use descriptive statistics and plots for exploratory data analysis, fit probability distributions to data, generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models. For multidimensional data analysis, Statistics and Machine Learning Toolbox provides feature selection, stepwise regression, principal component analysis (PCA), regularization, and other dimensionality reduction methods

• Author : Anonim
• Publisher : Unknown
• Release : 15 June 2021

• Author : Giuseppe Ciaburro
• Publisher : Packt Publishing Ltd
• Release : 28 August 2017

Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to

• Author : Supriya Salve
• Publisher : diplom.de
• Release : 23 March 2017

Breast cancer is the most common type of cancer in women, which also causes the most cancer deaths among them today. Mammography is the only reliable method to detect breast cancer in the early stage among all diagnostic methods available currently. Breast cancer can occur in both men and women and is defined as an abnormal growth of cells in the breast that multiply uncontrollably. The main factors which cause breast cancer are either hormonal or genetic. Masses are quite

• Author : J Abbel
• Publisher : Unknown
• Release : 28 May 2020

MATLAB enables the design of artificial intelligence models through three essential pillars: Machine Learning, Deep Learning and Data Science. Using MATLAB, engineers and other experts have deployed thousands of machine learning applications. Automated machine learning (AutoML) generate automatically functionalities from training data and optimize models using hyperparameter fitting techniques such as Bayesian optimization. Use specialized functionalities extraction techniques, such as wavelet dispersion for signal or image data, and functionalities selection techniques, such as neighbor component analysis (NCA) or sequential functionalities

• Author : Vivian Siahaan,Rismon Hasiholan Sianipar
• Publisher : BALIGE PUBLISHING
• Release : 03 March 2021

In this book, you will learn how to use NumPy, Pandas, OpenCV, Scikit-Learn and other libraries to how to plot graph and to process digital image. Then, you will learn how to classify features using Perceptron, Adaline, Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN) models. You will also learn how to extract features using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel Principal Component Analysis (KPCA) algorithms and use

• Author : Falai Li
• Publisher : Unknown
• Release : 15 June 1997

• Author : Ansel C. Ugural
• Publisher : Taylor & Francis
• Release : 29 March 2016

Analyze and Solve Real-World Machine Design Problems Using SI Units Mechanical Design of Machine Components, Second Edition: SI Versionstrikes a balance between method and theory, and fills a void in the world of design. Relevant to mechanical and related engineering curricula, the book is useful in college classes, and also serves as a reference for practicing engineers. This book combines the needed engineering mechanics concepts, analysis of various machine elements, design procedures, and the application of numerical and computational tools.

• Author : Ansel C. Ugural
• Publisher : Taylor & Francis
• Release : 03 September 2018

Analyze and Solve Real-World Machine Design Problems Using SI Units Mechanical Design of Machine Components, Second Edition: SI Version strikes a balance between method and theory, and fills a void in the world of design. Relevant to mechanical and related engineering curricula, the book is useful in college classes, and also serves as a reference for practicing engineers. This book combines the needed engineering mechanics concepts, analysis of various machine elements, design procedures, and the application of numerical and computational

• Author : Atif Iqbal,Shaikh Moinoddin,Bhimireddy Prathap Reddy
• Publisher : John Wiley & Sons
• Release : 22 April 2021

A comprehensive text, combining all important concepts and topics of Electrical Machines and featuring exhaustive simulation models based on MATLAB/Simulink Electrical Machine Fundamentals with Numerical Simulation using MATLAB/Simulink provides readers with a basic understanding of all key concepts related to electrical machines (including working principles, equivalent circuit, and analysis). It elaborates the fundamentals and offers numerical problems for students to work through. Uniquely, this text includes simulation models of every type of machine described in the book, enabling

• Author : Anonim
• Publisher : Unknown
• Release : 15 June 1998

• Author : K.P. Soman,R. LOGANATHAN,V. AJAY
• Publisher : PHI Learning Pvt. Ltd.
• Release : 02 February 2009

Support vector machines (SVMs) represent a breakthrough in the theory of learning systems. It is a new generation of learning algorithms based on recent advances in statistical learning theory. Designed for the undergraduate students of computer science and engineering, this book provides a comprehensive introduction to the state-of-the-art algorithm and techniques in this field. It covers most of the well known algorithms supplemented with code and data. One Class, Multiclass and hierarchical SVMs are included which will help the students

• Author : G. Peck
• Publisher : Createspace Independent Publishing Platform
• Release : 02 November 2017

Statistics and Machine Learning Toolbox provides functions and apps to describe, analyze, and model data. You can use descriptive statistics and plots for exploratory data analysis, fit probability distributions to data, generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms let you draw inferences from data and build predictive models. For multidimensional data analysis, Statistics and Machine Learning Toolbox provides feature selection, stepwise regression, principal component analysis (PCA), regularization, and other dimensionality reduction methods