Advances On Machine And Deep Learning Techniques In Modern Strategies
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Advances On Machine And Deep Learning Techniques In Modern Strategies
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Author : Mr.Chitra Sabapathy Ranganathan
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-04-02
Advances On Machine And Deep Learning Techniques In Modern Strategies written by Mr.Chitra Sabapathy Ranganathan and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.
Mr.Chitra Sabapathy Ranganathan, Associate Vice President, Mphasis Corporation, Arizona, USA
Deep Learning Techniques And Optimization Strategies In Big Data Analytics
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Author : Thomas, J. Joshua
language : en
Publisher: IGI Global
Release Date : 2019-11-29
Deep Learning Techniques And Optimization Strategies In Big Data Analytics written by Thomas, J. Joshua and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Modern Deep Learning For Tabular Data
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Author : Andre Ye
language : en
Publisher: Apress
Release Date : 2022-12-27
Modern Deep Learning For Tabular Data written by Andre Ye and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Computers categories.
Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain – tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data – an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs – Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks – through both their ‘default’ usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability. Each chapter comes with extensive visualization, code, and relevant research coverage. Modern Deep Learning for Tabular Data is one of the first of its kind – a wide exploration of deep learning theory and applications to tabular data, integrating and documenting novel methods and techniques in the field. This book provides a strong conceptual and theoretical toolkit to approach challenging tabular data problems. What You Will Learn Important concepts and developments in modern machine learning and deep learning, with a strong emphasis on tabular data applications. Understand the promising links between deep learning and tabular data, and when a deep learning approach is or isn’t appropriate. Apply promising research and unique modeling approaches in real-world data contexts. Explore and engage with modern, research-backed theoretical advances on deep tabular modeling Utilize unique and successful preprocessing methods to prepare tabular data for successful modelling. Who This Book Is ForData scientists and researchers of all levels from beginner to advanced looking to level up results on tabular data with deep learning or to understand the theoretical and practical aspects of deep tabular modeling research. Applicable to readers seeking to apply deep learning to all sorts of complex tabular data contexts, including business, finance, medicine, education, and security.
Artificial Intelligence And Deep Learning In Pathology
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Author : Stanley Cohen
language : en
Publisher: Elsevier Health Sciences
Release Date : 2020-06-02
Artificial Intelligence And Deep Learning In Pathology written by Stanley Cohen and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Medical categories.
Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Advances In Deep Learning
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Author : M. Arif Wani
language : en
Publisher: Springer
Release Date : 2019-03-14
Advances In Deep Learning written by M. Arif Wani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-14 with Technology & Engineering categories.
This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.
How Machine Learning Is Innovating Today S World
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Author : Arindam Dey
language : en
Publisher: John Wiley & Sons
Release Date : 2024-06-18
How Machine Learning Is Innovating Today S World written by Arindam Dey and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-18 with Computers categories.
Provides a comprehensive understanding of the latest advancements and practical applications of machine learning techniques. Machine learning (ML), a branch of artificial intelligence, has gained tremendous momentum in recent years, revolutionizing the way we analyze data, make predictions, and solve complex problems. As researchers and practitioners in the field, the editors of this book recognize the importance of disseminating knowledge and fostering collaboration to further advance this dynamic discipline. How Machine Learning is Innovating Today's World is a timely book and presents a diverse collection of 25 chapters that delve into the remarkable ways that ML is transforming various fields and industries. It provides a comprehensive understanding of the practical applications of ML techniques. The wide range of topics include: An analysis of various tokenization techniques and the sequence-to-sequence model in natural language processing explores the evaluation of English language readability using ML models a detailed study of text analysis for information retrieval through natural language processing the application of reinforcement learning approaches to supply chain management the performance analysis of converting algorithms to source code using natural language processing in Java presents an alternate approach to solving differential equations utilizing artificial neural networks with optimization techniques a comparative study of different techniques of text-to-SQL query conversion the classification of livestock diseases using ML algorithms ML in image enhancement techniques the efficient leader selection for inter-cluster flying ad-hoc networks a comprehensive survey of applications powered by GPT-3 and DALL-E recommender systems' domain of application reviews mood detection, emoji generation, and classification using tokenization and CNN variations of the exam scheduling problem using graph coloring the intersection of software engineering and machine learning applications explores ML strategies for indeterminate information systems in complex bipolar neutrosophic environments ML applications in healthcare, in battery management systems, and the rise of AI-generated news videos how to enhance resource management in precision farming through AI-based irrigation optimization. Audience The book will be extremely useful to professionals, post-graduate research scholars, policymakers, corporate managers, and anyone with technical interests looking to understand how machine learning and artificial intelligence can benefit their work.
Advances On Machine And Deep Learning Techniques In Modern Era
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Author : Dr.T.Arumuga Maria Devi
language : en
Publisher: SK Research Group of Companies
Release Date : 2023-05-17
Advances On Machine And Deep Learning Techniques In Modern Era written by Dr.T.Arumuga Maria Devi and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-17 with Computers categories.
Dr.T.Arumuga Maria Devi, Assistant Professor, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.V.S.Jeyalakshmi, Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.S.Kowsalya, Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. Mrs.V.Bhavani, Assistant Professor, Department of Computer Applications, Mannar Thirumalai Naicker College (Autonomous), Madurai, Tamil Nadu, India.
Concepts And Real Time Applications Of Deep Learning
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Author : Smriti Srivastava
language : en
Publisher: Springer Nature
Release Date : 2021-09-23
Concepts And Real Time Applications Of Deep Learning written by Smriti Srivastava and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Technology & Engineering categories.
This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.
Artificial Intelligence A Modern Approach
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Author : Anderson Coen
language : en
Publisher:
Release Date : 2020-05-25
Artificial Intelligence A Modern Approach written by Anderson Coen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-25 with categories.
Artificial Intelligence a Modern Approach It is no doubt that machine learning, deep learning, and artificial intelligence have made a lot of buzz in the technology world. Nevertheless, technological advancements have made deep learning, ML, and AI a part of our regular lives, unlike most other buzz words, which we tend to forget easily. Apart from that, AI is always here to stay. That's the main reason why if you are wanting to learn more about it, you need to maximize your learning. What better way to do this than a book bundle that brings you from zero to a future proof AI geek? This book has arrived to gear you with a basic, timely grasp of AI as well as its impact. The author offers a non-technical and engaging to vital aspects like natural language processing, deep learning, machine learning, and robotics, among others. Apart from helping you through real-world case studies and implementation steps, the author utilizes his knowledge to develop on the massive queries surrounding AI. Those include ethics, societal trends, and future impact AI will have on daily life, company structures, and world governments. Allow this book to guide you to learn the following topics: An Introduction to Artificial Intelligence Building a System The Fields Best Primed for Artificial Intelligence Successful AI Business Strategy Further Strengthening the AI Business Strategy How To Build a Machine Learning Model Benefits of AI for Businesses Facebook, Amazon, Google, and other tech giants today are far from the only companies on which AI has had - and will continue to have - a substantial outcome. AI is considered a present and the future of your business. Improving your expertise on the subject will prove precious to your preparation for the future of technology. This book is the indispensable handbook that you have been looking for. Well, stress no more! Buy this book and also learn all... and DOWNLOAD IT NOW!
Artificial Intelligence And Deep Learning For Decision Makers
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Author : Kaur Dr. Jagreet
language : en
Publisher: BPB Publications
Release Date : 2019-12-28
Artificial Intelligence And Deep Learning For Decision Makers written by Kaur Dr. Jagreet and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-28 with Computers categories.
Learn modern-day technologies from modern-day technical giants.KEY FEATURES1. Real-world success and failure stories of artificial intelligence explained2. Understand concepts of artificial intelligence and deep learning methods 3. Learn how to use artificial intelligence and deep learning methods4. Know how to prepare dataset and implement models using industry leading Python packages 5. You'll be able to apply and analyze the results produced by the models for predictionDESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. WHAT WILL YOU LEARN How to use the algorithms written in the Python programming language to design models and perform predictions in general datasetsUnderstand use cases in different industries related to the implementation of artificial intelligence and deep learning methodsLearn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methodsWHO THIS BOOK IS FORThis book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods.Table of Contents1. Artificial Intelligence and Deep Learning2. Data Science for Business Analysis3. Decision Making4. Intelligent Computing Strategies By Google 5. Cognitive Learning Services in IBM Watson6. Advancement web services by Baidu 7. Improved Social Business by Facebook8. Personalized Intelligent Computing by Apple9. Cloud Computing Intelligent by MicrosoftAbout the AuthorDr. Jagreet KaurDr. Jagreet Kaur is a doctorate in computer science and engineering. Her topic of thesis was "e;ARTIFICIAL INTELLIGENCE BASED ANALYTICAL PLATFORM FOR PREDICTIVE ANALYSIS IN HEALTH CARE."e; With more than 12 years of experience in academics and research, she is working in data wrangling, machine learning and deeplearning algorithms on large datasets, real-time data often in production environments for data science solutions and data products to get actionable insights for the last four years. She also possesses ten international publications and five national publications under her name.Her skill set includes data engineering skills (Hadoop, Apache Spark, Apache Kafka, Cassandra, Hive, Flume, Scoop, and Elasticsearch), programming skills (Python, Angularjs, D3.js , Machine Learning, and R), data science skills (Statistics, Machine Learning, NLP, NLTK, Artificial Intelligence, R, Python, Pandas, Sklearn, Hadoop, SQL, Statistical Modeling, Data Munging, Decision Science, Machine Learning, Graph Analysis, Text Mining and Optimization, and Web Scraping, Deep learning packages:- Theano, Keras, Tensorflow, Pytorch, Julia) and Algorithms Specialization (Regression Algorithms: Linear Regression, Random Forest Regressor, XGBoost, SVR, Ridge Regression, Lasso Regression, Neural Networks Classification Algorithms: Decision Trees, Random Forest Classifier, Support Vector Machines(SVM), Logistic Regression, KNN Classifier, Neural Network, Clustering Algorithms: K-Means, DBSCAN, Deep Learning Algorithms: Simple RNN, LSTM Network, GRU)Currently, she works as a Chief Operating Officer (COO) and Chief Data Scientist in Xenonstack. Under her Guidance, more than 400 projects are already developed and productionized which also includes more than 200 AI and data science projects. Navdeep Singh GillNaveed Singh Gill is a technology and solution architect having more than 15 years of experience in the IT and Telecom industry. For the past six years, he is working in big data analytics, automation and advanced analytics using machine learning and deep learning for planning and architecting of data science solutions and data products. He's also working in 3 As (Analytics, Automation, and AI), more focused on writing software for building data lake, analytics platform , NoSQL deployments, data migration, data modelling tasks, ML/DL on real-time data often in production environments.He started his career with HFCL Infotel as a network engineer for managing the technical network of Broadband Customers with Linux servers and Cisco routers. He also worked in Ericsson, where he handled the synchronization plan and implementation for synchronization of Microwave Network and Media Gateway, MSS, and Core Network. SSU Implementation Planning and Optimization with respect to IP RAN, Mobile Backhaul Solution- Optimization of Existing Microwave Network to Ethernet, Microwave Hybrid Solution, Convergence to all IP, SIU Implementation for conversion to IP of Existing BTS,GB over IP.His area of expertise includes Hadoop, Openstack, DevOps, Kubernetes, Dockers, Amazon web services, Apache Spark, Apache Storm, Apache Kafka, Hbase, Solr, Apache FlinkNutch, Mapreduce, Pig, Hive, Flume, Scoop, ElasticSearch, and programming expertise includes Python, Angular.js, and Node.js.