
Machine Learning Methods for Engineering Application Development
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Machine Learning Methods for Engineering Application Development
About this book
This book is a quick review of machine learning methods for engineeringapplications. It provides an introduction to the principles of machine learningand common algorithms in the first section. Proceeding chapters summarize andanalyze the existing scholarly work and discuss some general issues in this field.Next, it offers some guidelines on applying machine learning methods to softwareengineering tasks. Finally, it gives an outlook into some of the futuredevelopments and possibly new research areas of machine learning and artificialintelligence in general.Techniques highlighted in the book include: Bayesian models, supportvector machines, decision tree induction, regression analysis, and recurrent andconvolutional neural network. Finally, it also intends to be a reference book. Key Features: Describes real-world problems that can be solved using machine learningExplains methods for directly applying machine learning techniques to concrete real-world problemsExplains concepts used in Industry 4.0 platforms, including the use and integration of AI, ML, Big Data, NLP, and the Internet of Things (IoT). It does not require prior knowledge of the machine learning This book is meantto be an introduction to artificial intelligence (AI), machine earning, and itsapplications in Industry 4.0. It explains the basic mathematical principlesbut is intended to be understandable for readers who do not have a backgroundin advanced mathematics.
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Information
Table of contents
- Welcome
- Table of Content
- Title
- BENTHAM SCIENCE PUBLISHERS LTD.
- FOREWORD
- PREFACE
- List of Contributors
- Cutting Edge Techniques of Adaptive Machine Learning for Image Processing and Computer Vision
- Algorithm For Intelligent Systems
- Clinical Decision Support System for Early Prediction of Congenital Heart Disease using Machine learning Techniques
- A Review on Covid-19 Pandemic and Role of Multilingual Information Retrieval and Machine Translation for Managing its Effect
- An Empirical View of Genetic Machine Learning based on Evolutionary Learning Computations
- High-Performance Computing for Satellite Image Processing Using Apache Spark
- Artificial Intelligence and Covid-19: A Practical Approach
- Intelligent Personalized E-Learning Platform using Machine Learning Algorithms
- Automated Systems using AI in the Internet of Robotic Things: A New Paradigm for Robotics
- Missing Value Imputation and Estimation Methods for Arrhythmia Feature Selection Classification Using Machine Learning Algorithms
- Analysis of Abstractive Text Summarization with Deep Learning Technique
- Advanced Topics in Machine Learning