Machine Learning Algorithms And Their Use Cases
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Machine Learning Algorithms And Their Use Cases
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Author : Yuliana, S.Kom., M.Kom.
language : id
Publisher: Penerbit Widina
Release Date : 2025-03-26
Machine Learning Algorithms And Their Use Cases written by Yuliana, S.Kom., M.Kom. and has been published by Penerbit Widina this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Computers categories.
Di era digital yang serba cepat, Machine Learning telah menjadi kunci utama dalam mengolah data dan menciptakan teknologi cerdas. Buku ini membahas berbagai algoritma machine learning, bagaimana cara kerja mereka, serta bagaimana data menjadi bahan bakar utama dalam pengambilan keputusan otomatis. Dengan pendekatan sistematis, pembaca akan diperkenalkan pada dasar-dasar machine learning, mulai dari konsep statistik hingga penerapan teknologi terkini. Lebih dari sekadar teori, buku ini menghubungkan machine learning dengan inovasi nyata, termasuk dalam pengembangan teknologi robot. Bagaimana algoritma memungkinkan robot untuk berpikir, belajar, dan beradaptasi? Jawaban dari pertanyaan ini akan dikupas dalam bab-bab menarik yang mengulas interaksi antara kecerdasan buatan dan dunia fisik. Pembaca akan memahami bagaimana teknologi ini mengubah industri, mulai dari otomasi manufaktur hingga kendaraan otonom. Sebagai nilai tambah, buku ini menghadirkan berbagai use case study yang relevan dengan perkembangan industri modern. Dari analisis data dalam bisnis hingga pemanfaatan Al dalam kesehatan, setiap studi kasus memberikan wawasan mendalam tentang penerapan machine learning dalam dunia nyata. Buku ini bukan hanya panduan teknis, tetapi juga inspirasi bagi siapa saja yang ingin menggali lebih dalam potensi kecerdasan buatan di masa depan.
The Hitchhiker S Guide To Machine Learning Algorithms
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Author : Devin Schumacher
language : en
Publisher: SERP Media
Release Date : 2023-07-26
The Hitchhiker S Guide To Machine Learning Algorithms written by Devin Schumacher and has been published by SERP Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Computers categories.
Hello humans & welcome to the world of machines! Specifically, machine learning & algorithms. We are about to embark on an exciting adventure through the vast and varied landscape of algorithms that power the cutting-edge field of artificial intelligence. Machine learning is changing the world as we know it. From predicting stock market trends and diagnosing diseases to powering the virtual assistants in our smartphones and enabling self-driving cars, and picking up the slack on your online dating conversations. What makes this book unique is its structure and depth. With 100 chapters, each dedicated to a different machine learning concept, this book is designed to be your ultimate guide to the world of machine learning algorithms. Whether you are a student, a data science professional, or someone curious about machine learning, this book aims to provide a comprehensive overview that is both accessible and in-depth. The algorithms covered in this book span various categories including: Classification & Regression: Learn about algorithms like Decision Trees, Random Forests, Support Vector Machines, and Logistic Regression which are used to classify data or predict numerical values. Clustering: Discover algorithms like k-Means, Hierarchical Clustering, and DBSCAN that group data points together based on similarities. Neural Networks & Deep Learning: Dive into algorithms and architectures like Perceptrons, Convolutional Neural Networks (CNN), and Long Short-Term Memory Networks (LSTM). Optimization: Understand algorithms like Gradient Descent, Genetic Algorithms, and Particle Swarm Optimization which find the best possible solutions in different scenarios. Ensemble Methods: Explore algorithms like AdaBoost, Gradient Boosting, and Random Forests which combine the predictions of multiple models for improved accuracy. Dimensionality Reduction: Learn about algorithms like Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) which reduce the number of features in a dataset while retaining important information. Reinforcement Learning: Get to know algorithms like Q-learning, Deep Q-Network (DQN), and Monte Carlo Tree Search which are used in systems that learn from their environment. Each chapter is designed as a standalone introduction to its respective algorithm. This means you can start from any chapter that catches your interest or proceed sequentially. Along with the theory, practical examples, applications, and insights into how these algorithms work under the hood are provided. This book is not just an academic endeavor but a bridge that connects theory with practical real-world applications. It's an invitation to explore, learn, and harness the power of algorithms to solve complex problems and make informed decisions. Fasten your seat belts as we dive into the mesmerizing world of machine learning algorithms. Whether you are looking to expand your knowledge, seeking inspiration, or in pursuit of technical mastery, this book should sit on your coffee table and make you look intelligent in front of all invited (and uninvited) guests.
Artificial Intelligence And Machine Learning For Edge Computing
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Author : Rajiv Pandey
language : en
Publisher: Academic Press
Release Date : 2022-04-26
Artificial Intelligence And Machine Learning For Edge Computing written by Rajiv Pandey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-26 with Science categories.
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Machine Learning Ai
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Author : Prathmesh Yelne
language : en
Publisher: Codegyan
Release Date : 2023-08-01
Machine Learning Ai written by Prathmesh Yelne and has been published by Codegyan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-01 with Education categories.
Discover the extraordinary possibilities of machine learning and artificial intelligence in this groundbreaking exploration. From self-driving cars to virtual assistants, this book delves into the fascinating world of algorithms and how they are transforming industries and revolutionizing our lives. Explore the inner workings of neural networks, deep learning models, and predictive analytics, and witness the profound impact they have on decision-making, problem-solving, and data analysis. Whether you're a novice or an expert in the field, prepare to be captivated by the limitless potential of machine learning and AI.
Machine Learning For Decision Sciences With Case Studies In Python
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Author : S. Sumathi
language : en
Publisher: CRC Press
Release Date : 2022-07-08
Machine Learning For Decision Sciences With Case Studies In Python written by S. Sumathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-08 with Computers categories.
This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learning. This book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.
Machine Learning For Data Science Handbook
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Author : Lior Rokach
language : en
Publisher: Springer Nature
Release Date : 2023-08-17
Machine Learning For Data Science Handbook written by Lior Rokach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Computers categories.
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
Artificial Intelligence Theory Models And Applications
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Author : P Kaliraj
language : en
Publisher: CRC Press
Release Date : 2021-10-21
Artificial Intelligence Theory Models And Applications written by P Kaliraj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-21 with Computers categories.
This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.
Machine Learning Algorithms For Industrial Applications
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Author : Santosh Kumar Das
language : en
Publisher: Springer Nature
Release Date : 2020-07-18
Machine Learning Algorithms For Industrial Applications written by Santosh Kumar Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-18 with Technology & Engineering categories.
This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.
Introduction To Machine Learning In The Cloud With Python
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Introduction To Machine Learning In The Cloud With Python written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.
This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.
Deep Reinforcement Learning Emerging Trends In Macroeconomics And Future Prospects
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Author : Tohid Atashbar
language : en
Publisher: International Monetary Fund
Release Date : 2022-12-16
Deep Reinforcement Learning Emerging Trends In Macroeconomics And Future Prospects written by Tohid Atashbar and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-16 with Business & Economics categories.
The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how deep reinforcement learning can be used to study a variety of economic problems, including optimal policy-making, game theory, and bounded rationality. In this paper, after a theoretical introduction to deep reinforcement learning and various DRL algorithms, we provide an overview of the literature on deep reinforcement learning in economics, with a focus on the main applications of deep reinforcement learning in macromodeling. Then, we analyze the potentials and limitations of deep reinforcement learning in macroeconomics and identify a number of issues that need to be addressed in order for deep reinforcement learning to be more widely used in macro modeling.