Machine Learning For Data Science Using Ml Algorithms For Predictive Modeling
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Machine Learning For Data Science Using Ml Algorithms For Predictive Modeling
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Author : Dr. Rachit Adhvaryu
language : en
Publisher: Xoffencerpublication
Release Date : 2024-05-14
Machine Learning For Data Science Using Ml Algorithms For Predictive Modeling written by Dr. Rachit Adhvaryu and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-14 with Computers categories.
Machine learning is an area of artificial intelligence that focuses on teaching computers how to learn without being explicitly instructed to do so. This ability allows computers to acquire knowledge and competence via experience rather than being taught to do so. In recent years, as a consequence of the many different applications it has in a broad variety of fields, it has become an increasingly important topic of debate as a result of the multiple practical uses it has. Throughout the course of this blog, we will discuss how machine learning is being utilized to address difficulties in the real world, as well as study the principles of machine learning and go into more advanced topics. Whether you are a newbie interested in learning about machine learning or an experienced data scientist wishing to keep up to speed on the latest breakthroughs in the field, we hope that you will find something here that is of interest to you. If you are a novice interested in learning about machine learning, go here. Machine learning is an application of artificial intelligence that makes use of statistical methods to teach computers how to learn on their own and make judgements without being expressly programmed to do so. This is accomplished via the use of statistical methods. It is predicated on the notion that computers are able to learn from data, spot patterns, and make decisions with relatively little input from human beings
Machine Learning For Data Science Using Ml Algorithms For Predictive Modeling
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Author : Dilip Siddareddy
language : en
Publisher: Xoffencerpublication
Release Date : 2023-10-30
Machine Learning For Data Science Using Ml Algorithms For Predictive Modeling written by Dilip Siddareddy and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-30 with Computers categories.
Because of the advancements that have been made in machine learning, the world is being changed in ways that are difficult to conceive. If you stop for a second and take a good look around, you'll see that the area of data science is everywhere you turn. Take, for example, Alexa from Amazon; she is an artificial intelligence that has been developed to be as simple and straightforward to use as is humanly conceivable. There are many other digital assistants similar to Alexa, such as Google Assistant, Cortana, and so on. Alexa is not the only one of its sort. Therefore, the question of why they were formed in the first place is the most crucial one to ask; the question of how they developed is the second most important one to ask. In any event, we are going to make an attempt to study each and every one of these issues, and we are also going to make an effort to devise answers that are both logical and technological in nature. Within the scope of this discussion, the question that has to be inquired about first and foremost is, "What exactly are Machine Learning and Data Science?" A widespread misconception is that data science and machine learning are interchangeable terms for the same thing. Those people do have a point, to some extent, considering that data science is nothing more than taking a huge amount of data and analyzing it using a variety of machine learning approaches, methodologies, and technologies. Therefore, in order to become an expert in data science, you need to have a solid understanding of mathematics and statistics, in addition to a profound comprehension of the area that you intend to specialize in. To be more specific, what does it mean to have "subject expertise"? Subject expertise is nothing more than the knowledge necessary about a given topic in order to be able to abstract and calculate the data that pertains to that field, as the name of this type of expertise indicates. In a nutshell, these three concepts are considered as the foundations of data science, and if you are successful in mastering all of them, then you should rejoice yourself because you have achieved the level of an A-level data scientist.
Fundamentals Of Machine Learning For Predictive Data Analytics
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Author : John D. Kelleher
language : en
Publisher: MIT Press
Release Date : 2015-07-31
Fundamentals Of Machine Learning For Predictive Data Analytics written by John D. Kelleher and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-31 with Computers categories.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Data Science And Artificial Intelligence
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Author : Chutiporn Anutariya
language : en
Publisher: Springer Nature
Release Date : 2024-11-08
Data Science And Artificial Intelligence written by Chutiporn Anutariya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-08 with Computers categories.
This book constitutes the proceedings of the Second refereed proceedings of the Second International Conference on Data Science and Artificial Intelligence, DSAI 2024, held in Medan, Indonesia, during November 13–15, 2024. The 18 full papers, 2 short papers and 3 invited talks were included in this book were carefully reviewed and selected from 69 submissions. They are organized in the following topical sections: Keynote Presentations; Natural and Sign Language Processing; Applications of Data Science and Artificial Intelligence; Affective Computing and AI Games; Embedded AI and Applications; Data Science; AI and Healthcare.
Machine Learning Image Processing Network Security And Data Sciences
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Author : Naveen Chauhan
language : en
Publisher: Springer Nature
Release Date : 2024-06-10
Machine Learning Image Processing Network Security And Data Sciences written by Naveen Chauhan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-10 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2023, held in Hamirpur, India, during December 21–22, 2023. The 29 full papers included in this book were carefully reviewed and selected from 173 submissions. They were organized in topical sections as follows: Machine Learning; Image Processing; Network Security; and Data Sciences.
Practical Data Analytics For Innovation In Medicine
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Author : Gary D. Miner
language : en
Publisher: Academic Press
Release Date : 2023-02-08
Practical Data Analytics For Innovation In Medicine written by Gary D. Miner and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-08 with Science categories.
Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. - Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis - Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today's medical issues and basic research - Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate
Advanced Prognostic Predictive Modelling In Healthcare Data Analytics
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Author : Sudipta Roy
language : en
Publisher: Springer Nature
Release Date : 2021-04-22
Advanced Prognostic Predictive Modelling In Healthcare Data Analytics written by Sudipta Roy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-22 with Technology & Engineering categories.
This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.
Data Science In The Medical Field
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Author : Seifedine Kadry
language : en
Publisher: Elsevier
Release Date : 2024-09-30
Data Science In The Medical Field written by Seifedine Kadry and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Business & Economics categories.
Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage. - Shows how improving automated analytical techniques can be used to generate new information from data for healthcare applications - Combines a number of related fields, with a particular emphasis on machine learning, big data analytics, statistics, pattern recognition, computer vision, and semantic web technologies - Provides information on the cutting-edge data science tools required to accelerate innovation for healthcare organizations and patients by reading this book
Emerging Technologies In Computing
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Author : Mahdi H. Miraz
language : en
Publisher: Springer Nature
Release Date : 2020-09-28
Emerging Technologies In Computing written by Mahdi H. Miraz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-28 with Computers categories.
This book constitutes the refereed conference proceedings of the Third International Conference on Emerging Technologies in Computing, iCEtiC 2020, held in London, UK, in August 2020. Due to VOVID-19 pandemic the conference was helt virtually.The 25 revised full papers were reviewed and selected from 65 submissions and are organized in topical sections covering blockchain and cloud computing; security, wireless sensor networks and IoT; AI, big data and data analytics; emerging technologies in engineering, education and sustainable development.
Machine Learning In Educational Sciences
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Author : Myint Swe Khine
language : en
Publisher: Springer Nature
Release Date : 2024-02-24
Machine Learning In Educational Sciences written by Myint Swe Khine and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Education categories.
This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.