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What is Machine Learning (ML)

Handbook of Research on Teaching With Virtual Environments and AI
Is specifically involved with the training of Neural Networ and evaluation of accuracy of predictions.
Published in Chapter:
How Can Education Use Artificial Intelligence?: A Brief History of AI, Its Usages, Its Successes, and Its Problems When Applied to Education.
Claudio Pacchiega (Edu3d, Italy)
Copyright: © 2021 |Pages: 33
DOI: 10.4018/978-1-7998-7638-0.ch024
Abstract
AI, artificial intelligence, has recently made a big leap, especially in the field of ANI (artificial narrowed intelligence), meaning that now we are starting to have decent tools that can be useful in teaching. After the surge in importance of the distant learning techniques due to the COVID-19 pandemic in 2020, many educators have found themselves lost in dealing with an overwhelming excess of electronic information from their students, either via chat, email, documents, videos, or multimedia material. This chapter tries to delve into the difficulties of using affordable techniques for generating valid synthetic information such as rating homework or understanding if students are correctly following distant lessons. Since this is still an early subject, much more study and tests must be done to understand the full usability of automated AI tools in this (educational) context.
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Deep Learning in Instructional Analysis, Design, Development, Implementation, and Evaluation (ADDIE)
The machine learning (e.g., ML) is the part of AI, that can learn and improve learning automatically using the data. Some of the real world examples of the ML include virtual personal assistants, video surveillance, malware filtering, etc.
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The Use of Artificial Intelligence in the Food Industry: From Recipe Generation to Quality Control
ML is a subset of AI that trains algorithms to make predictions and decisions based on input data, rather than being explicitly programmed to perform a specific task.
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Non-Technological and Technological (SupTech) Innovations in Strengthening the Financial Supervision
A subset of artificial intelligence aimed at enabling computers to analyze and learn from huge amounts of data with a view to making forecasts.
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The Role of Digital Economies in the Development and Growth in Asian Business Models
ML is a branch of Artificial Intelligence that uses statistical techniques or algorithms to allow a computer to become better at what it does. The computer classifies patterns in behavior or speech, such as, it notes those differences to “learn” more about a specific user or set of users.
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Open Challenges and Research Issues of XAI in Modern Smart Cities
A type of AI that enables machines to learn from data without being explicitly programmed, and improve their performance over time.
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A Platform for the Promotion of Energy Efficiency and Monitoring in Hotel Units
Automated learning concept that uses different methods and models to learn from past experience through the analysis of historical data.
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Investigating the Service Quality of Chatbots on Telecom Service Providers' Websites and Apps
A field in computer science that focuses on developing algorithms that can learn and improve from data without being explicitly programmed (Mahesh, 2020 AU133: The in-text citation "Mahesh, 2020" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ; Bertolini et al., 2021 AU134: The in-text citation "Bertolini et al., 2021" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ). The aim is to create intelligent machines that can learn from experience and make predictions or decisions.
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Decision Support Approach for Assessing of Rail Transport: Methods Based on AI and Machine Learning
Learning is a very broad term that describes the process by which humans or machines can increase their knowledge. Machine learning relies on the application of inductive, deductive, abductive, or analogous techniques. To learn is to reason, to discover analogies and similarities, to generalize or particularize an experience, to take advantage of past failures and errors for subsequent reasoning. New learning is used to solve new problems, accomplish a new task, or increase performance in accomplishing an existing task, explain a situation or predict behaviour. ML facilitates the transfer of knowledge, in particular from experimental examples. It contributes to the development of knowledge bases of Knowledge Base Systems while reducing the intervention of the knowledge engineer (cognitician). In our approach, the learning exploits the historical database (accident or incident scenarios) to generate new knowledge that can help certification experts to assess the degree of safety of a new transport system.
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Predicting Cryptocurrency Prices Model Using a Stacked Sparse Autoencoder and Bayesian Optimization
Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn and make predictions or decisions based on data.
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Instructing AI Ethics and Human Rights
ML an application of AI it gives devices the ability to learn from their experiences and improve their self without doing any coding.
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A Summary on 5G and Future 6G Internet of Things
A subfield of artificial intelligence (AI) that enables machine systems to automatically learn, self-improvement from past experience, and make decisions without being explicitly programmed.
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Artificial Intelligence and Image Analysis for the Identification of Endometrial Malignancies: A Comparative Study
It is a subset of artificial intelligence. The main characteristic of this discipline is related to the study of algorithms (including statistical models) that can be used by computerized systems in order to perform learning and recognition tasks however without using extensive and explicit instructions, instead learning of patterns and inference is used.
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Early Beginnings of AI: The Field of Research in Computer Science
Machine Learning is the field of Artificial Intelligence that studies developing algorithms that help AI machines learn and enhance from experience.
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Machine Learning Applications for Vibration-Based Structural Health Monitoring
Subset of AI, that is the development of algorithms and statistical models used by computer systems in order to effectively perform a specific task without using explicit instructions.
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Chatbots in Digital Marketing: Enhanced Customer Experience and Reduced Customer Service Costs
Machine learning is an area of artificial intelligence that allows computer systems to learn and enhance their performance via experience, without explicit being programmed.
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Redefining Traditional Pedagogy: The Integration of Machine Learning in the Contemporary Language Education Classroom
Computer algorithms which improve through the use of data, without following explicit instructions. Part of artificial intelligence.
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Efficiency Assessment and Optimization in Renewable Energy Systems Using Data Envelopment Analysis
ML is a subset of artificial intelligence (AI) that focuses on developing algorithms and statistical models enabling computer systems to improve their performance on a specific task through learning from data and experiences. ML algorithms enable computers to identify patterns, make predictions, and improve their decision-making without being explicitly programmed for each task. It finds applications in various fields, including data analysis, pattern recognition, natural language processing, and autonomous systems.
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Transforming Education With the Power of Artificial Intelligence: Case Studies
A subfield of Artificial Intelligence that involves the development of systems with autonomous learning. Machine learning implies that computers accumulate experience and improve their performance using data.
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Electronic Health Records (EHR) and Clinical Decision Support Systems: Integrating AI Solutions
A branch of AI that focuses on the use of statistical models and techniques to enable computers to become better at tasks over time.
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Integrating Content Authentication Support in Media Services
Scientific discipline that investigates algorithms and methods aiming at giving machines the ability to learn from experience (without being explicitly programed), in order to respond autonomously on specific tasks and automate various data-handling processes.
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The Image as Big Data Toolkit: An Application Case Study in Image Analysis, Feature Recognition, and Data Visualization
Machine Learning techniques may be used for a variety of image processing tasks including feature extraction, scene analysis, object detection, hypothesis generation, model building and model instantiation.
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Towards an Automated, Vigilant, and Strategic HRM Function in Industry 5.0
A technology that induces the learning capabilities within the machines through algorithms and computing power for generating predictive capability.
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Automated Assessment and Feedback in Higher Education Using Generative AI
A subset of AI, Machine Learning involves algorithms that enable computers to learn and adapt from experience without being explicitly programmed. ML focuses on developing systems that can access and use data to learn for themselves.
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Examining the Task - Technology Fit of ChatGPT for Healthcare Services
A type of artificial intelligence that learns from data without being explicitly programmed (Binkhonain & Zhao, 2019 AU98: The in-text citation "Binkhonain & Zhao, 2019" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ; Bunod et al., 2022 AU99: The in-text citation "Bunod et al., 2022" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ; Mahesh, 2020 AU100: The in-text citation "Mahesh, 2020" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
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Achieving Ambient Intelligence in Addressing the COVID-19 Pandemic Using Fog Computing-Driven IoT
It is the study of certain rigorous techniques which escalates the performance by gaining experience and via utilization of several data.
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Deep Learning Approaches for Affective Computing in Text
Is a computer science field that enables computers to learn without explicit programming.
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Systematic Literature Review: XAI and Clinical Decision Support
An application of AI that enables systems to learn and improve from experience without being explicitly programmed. Machine learning focuses on developing computer programs that can access data and use it to learn for themselves.
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Embracing Technological Advancements: A Futuristic Approach to Hospitality Management
ML is a branch of Artificial Intelligence (AI) that helps machines to learn from the collected data and past experiences. In ML, machines make predictions recognizing the similar pattern from the data.
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Exhibiting App and Analysis for Biofeedback-Based Mental Health Analyzer
Is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
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Generative AI in Higher Education
A subset of AI where algorithms use data to learn and make predictions or decisions. Instead of being explicitly programmed, these algorithms improve automatically through experience.
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Navigating the Metaverse: A Comprehensive Guide to Marketing, Branding, and Innovation
Machine learning is a subset of artificial intelligence that involves algorithms and statistical models allowing computer systems to improve their performance on a specific task over time without explicit programming.
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Customer Service Bots: Enhancing Support and Personalization
Machine Learning is a subset of AI that focuses on the development of algorithms and statistical models that enable computers to improve their performance on specific tasks through learning from data.
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Innovative Advancements in Big Data Analytics: Navigating Future Trends With Hadoop Integration
A subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models enabling computer systems to improve their performance on tasks without explicit programming. ML involves the automatic learning of patterns and insights from data, allowing systems to make predictions, classifications, or decisions based on experience and training rather than explicit programming.
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Fairness Challenges in Artificial Intelligence
ML commonly used alongside AI and is a subset of AI. ML refers to systems that can learn from data, i.e., systems that get smarter by learning over time without direct human intervention.
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Machine Learning for Image Classification
A powerful tool for pattern classification. It uses the theory of statistics in building mathematical models, and programs computers to optimize a performance criterion using example data or past experience.
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Cloud Security: Challenges, Solutions, and Future Directions: Navigating the Complexities of securing Cloud
A branch of AI and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.
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Data Privacy vs. Data Security
A computer program having the capability to learn and adapt to new data without human assistance.
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AI and OpenAI in Education: Unveiling the Future of Learning and Teaching
A subset of AI that uses algorithms and statistical models to enable computers to perform tasks without explicit instructions by relying on patterns and inference.
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Machine Learning Approaches to Automated Medical Decision Support Systems
Subset of Artificial Intelligence field focused on the acquisition and process of data aiming to produce knowledge and reasonable explanations.
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Role of Digital Identity in Advancing Global Health: A 360 Perspective
Type of AI that enables self-learning from data and applies that learning without human intervention by identifying patterns in data, especially diverse and high-dimensional data. In this model, data is usually aggregated from several edge devices in a centralized server and trained.
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Using Online Digital Data to Infer Valuable Skills for the Modern Workforce
A branch of computer science that uses data and specific algorithms to imitate how humans think and learn.
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Exploratory Research of Cyber Security Dimensions: Selected Use Cases Analysis
It refers to the concept of training the machine with a given dataset to automate the system's decision-making and imitate the ways humans learn.
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Towards Fully Automated Decision-Making Systems for Precision Agriculture: Soil Sensing Technologies – “The Missing Link”
ML is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead.
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VLE Meets VW
Software algorithms that enable the application of AI techniques as the employ the processing of data to add value and incrementally improve automatically as they learn from the extracted information. The learning process is through the analysis of the masses of data available and identifying patterns while performing decisions based on the algorithm programmed by the AI developer.
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The Impact of News on Public-Private Partnership Stock Price in China via Text Mining Method
ML is a branch of artificial intelligence. ML is a way to realize AI. By using ML, users may solve AI problems. ML theory is mainly about designing and analyzing algorithms that enable computers to “learn” automatically. ML algorithm, as a means, allow users to predict unknown data.
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Recent Developments in Chatbot Usability and Design Methodologies
It is a sub field of artificial intelligence that identifies patterns in human conversations and can be used to create chatbots.
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Chatbot Implementation in a Steel Company in Russia: Towards a Model for Successful Chatbot Projects
A set of activities which leverage modern computer algorithms to process data and solve vast numbers of applicable or scientific tasks.
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Analysis of Ethical Development for Public Policies in the Acquisition of AI-Based Systems
AI subfield and evolving branch of computational algorithms that are designed to emulate human intelligence by learning from the surrounding environment.
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Machine Learning-Enabled Internet of Things Solution for Smart Agriculture Operations
Technology is a type of AI that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. ML algorithms use historical data as input to predict new output values.
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An Intelligent Virtual Medical Assistant for Healthcare Prediction
It is the subset of Artificial Intelligence which helps the system to learn from the dataset without having any specific programs.
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Deep Learning Applications in Agriculture: The Role of Deep Learning in Smart Agriculture
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed and in the process developing computer programs that can access data and use it to learn for themselves.
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Plant Disease Classification Using Deep Learning Techniques
ML is a subset of AI that involves training algorithms to make predictions or decisions based on input data, rather than being explicitly programmed to perform a specific task.
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Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software
A part of artificial intelligence that is the study of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as “training data,” in order to make predictions or decisions without being explicitly programmed to do so ( Wikipedia, 2021b ).
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Artificial Intelligence for Sustainable Humanitarian Logistics
A branch of AI that automates data-driven analytical modelling.
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AI-Driven Learning Analytics for Personalized Feedback and Assessment in Higher Education
is a subset of artificial intelligence (AI) that involves the development of algorithms and statistical models that enable computer systems to improve their performance on a specific task through learning from data, without being explicitly programmed.
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Building a Chatbot for Libraries
The development of algorithms that enable machines to mimic human intelligence.
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Enhancing Cloud Security: The Role of Artificial Intelligence and Machine Learning
Machine learning is a field of artificial intelligence (AI) that involves developing algorithms and models that enable computers to learn and improve their performance on tasks from data, rather than being explicitly programmed. In essence, it's the science of enabling computers to make predictions, recognize patterns, and make decisions based on data and experience.
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Digital Technology Deployment in Multi-National Enterprises
A type of artificial intelligence that enables self-learning from data and then applies that learning without the need for human intervention.
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Waste-to-Energy Solutions Harnessing IoT and ML for Sustainable Power Generation in Smart Cities
Is a subset of artificial intelligence (AI) that empowers computers to learn and improve from experience without being explicitly programmed. It enables systems to analyze data, identify patterns, and make informed decisions, allowing them to evolve and adapt to new information over time. ML algorithms leverage statistical techniques to enable machines to perform tasks and make predictions or decisions without explicit programming for each task.
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A Meta-Analytical Review of Deep Learning Prediction Models for Big Data
Machine learning is a new technology where machine learns from the past data in order to decide and work for future data, thus helps in process of automation.
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Explanations in Artificial Intelligence Decision Making: A User Acceptance Perspective
A set of AI techniques to develop computer systems that learn statistical regularities between inputs and outputs, thereby generating outputs from a set of inputs alone.
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Approval of Artificial Intelligence and Machine Learning Models to Solve Problems in Nonlinear Active Suspension Systems
The machine learning field is a branch of artificial intelligence (AI) that focuses on using data and algorithms to mimic how people learn, gradually increasing the accuracy of its predictions.
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Ethical Considerations and Privacy Concerns in AI-Enabled Libraries
A subset of artificial intelligence where algorithms are programmed to learn from data and improve themselves over time without explicit programming. Machine learning models can detect patterns in data and make predictions. Libraries can leverage ML for tasks like personalized book recommendations based on borrowing history.
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Explainable Safety Risk Management in Construction With Unsupervised Learning
A subset of AI that learns the input dataset using different algorithms for a variety of tasks.
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
Is a class of methods of Artificial Intelligence, whose characteristic feature is not a direct solution to the problem, but learning in the process of applying solutions to many similar tasks.
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Leveraging Ethics in Artificial Intelligence Technologies and Applications: E-Learning Management Systems in Namibia
Computer algorithms that mimic human intelligence capable of learning from the patterns of events happening in the surrounding environment.
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The Understanding of Spatial-Temporal Behaviors
A powerful tool for pattern classification. It uses the theory of statistics in building mathematical models, and programs computers to optimize a performance criterion using example data or past experience.
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Trustworthy Artificial Intelligence and Machine Learning: Implications on Users' Security and Privacy Perceptions
ML is a subset of AI that often uses statistical techniques to give machines the ability to “learn” from data without being explicitly given instructions for how to do so. This process is known as “training” a “model” using a learning “algorithm” that progressively improves model performance on a specific task.
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