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Advanced Interdisciplinary Applications Of Machine Learning Python Libraries For Data Science
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Book Synopsis Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science by : Soly Mathew Biju
Download or read book Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science written by Soly Mathew Biju and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science by : Biju, Soly Mathew
Download or read book Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science written by Biju, Soly Mathew and published by IGI Global. This book was released on 2023-09-13 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is approaching a point where big data will start to play a beneficial role in many industries and organizations. Today, analyzing data for new insights has become an everyday norm, increasing the need for data analysts to use efficient and appropriate tools to provide quick and valuable results to clients. Existing research in the field currently lacks a full coverage of all essential algorithms, leaving a knowledge void for practical implementation and code in Python with all needed libraries and links to datasets used. Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science serves as a one-stop book to help emerging data scientists gain hands-on skills needed through real-world data and completely up-to-date Python code. It covers all the technical details, from installing the needed software to importing libraries and using the latest data sets; deciding on the right model; training, testing, and evaluating the model; and including NumPy, Pandas, and matplotlib. With coverage on various machine learning algorithms like regression, linear and logical regression, classification, support vector machine (SVM), clustering, k-nearest neighbor, market basket analysis, Apriori, k-means clustering, and visualization using Seaborne, it is designed for academic researchers, undergraduate students, postgraduate students, executive education program leaders, and practitioners.
Book Synopsis Meta-Learning Frameworks for Imaging Applications by : Sharma, Ashok
Download or read book Meta-Learning Frameworks for Imaging Applications written by Sharma, Ashok and published by IGI Global. This book was released on 2023-09-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications, experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.
Book Synopsis Global Perspectives on Robotics and Autonomous Systems: Development and Applications by : Habib, Maki K.
Download or read book Global Perspectives on Robotics and Autonomous Systems: Development and Applications written by Habib, Maki K. and published by IGI Global. This book was released on 2023-08-01 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an increasing demand to develop intelligent robotics and autonomous systems to deal with dynamically changing and complex, unstructured, and unpredictable environments. Such robots should be able to handle task varieties, environment dynamics and goal variations, and their complexity. This also highlights the need for having intelligent robotics and autonomous systems with capabilities assuring reliable and robust functions resolving real-time complex problems that are associated with many applications across diverse domains. This requires unconventional ways to develop creative and innovative, energy-efficient, and eco- and environmentally friendly solutions that consider new ways of creative thinking while drawing inspiration from nature as a model leading to creating new designs, intelligent systems, intelligent structures/mechanisms, reconfigurability, and more. Global Perspectives on Robotics and Autonomous Systems: Development and Applications describes the evolution of robotics and autonomous systems, their development, their technologies, and their applications. This book discusses the concept of autonomy, requirements, and its role in shaping the behavior of these robots so that they can make their own effective and safe decisions and act on them reliably while assuring real-life requirements. Covering topics such as digital transformation, fused deposition modeling (FDM), and organizational unbundling process, this premier reference source is an essential resource for engineers, computer scientists, industry professionals, manufacturers, smart systems developers, data analysts, students and educators of higher educations, researchers, and academicians.
Book Synopsis Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management by : Kumar, Rajeev
Download or read book Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management written by Kumar, Rajeev and published by IGI Global. This book was released on 2023-09-25 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging technologies have become both crucibles and showrooms for the practical application of artificial intelligence, the internet of things, and cloud computing, and for integrating big data into everyday life. Is the digital world optimized and sustainable using intelligence systems, machine learning, and cyber security methods? This complex concoction of challenges requires new thinking of the synergistic utilization of intelligence systems, machine learning, deep learning and blockchain methods, data-driven decision-making with automation infrastructure, autonomous transportation, and connected buildings. Effective AI, Blockchain, and E-Governance Applications for Knowledge Discovery and Management provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications, including recent advances and challenges related to the concerns of security and privacy issues in deep learning with an emphasis on the current state-of-the-art methods, methodologies and implementation, attacks, and countermeasures. The book also discusses the challenges that need to be addressed for implementing DL-based security mechanisms that should have the capability of collecting or distributing data across several applications. Topics covered include skill development and tools for intelligence systems, deep learning, machine learning, blockchain, IoT, cloud computing, data ethics, and infrastructure. It is ideal for independent researchers, research scholars, scientists, libraries, industry experts, academic students, business associations, communication and marketing agencies, entrepreneurs, and all potential audiences with a specific interest in these topics.
Book Synopsis Multi-Disciplinary Applications of Fog Computing: Responsiveness in Real-Time by : Acharjya, Debi Prasanna
Download or read book Multi-Disciplinary Applications of Fog Computing: Responsiveness in Real-Time written by Acharjya, Debi Prasanna and published by IGI Global. This book was released on 2023-08-03 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, several fog computing applications have been developed like IoT-based healthcare, 5G, blockchains, autonomous driving, and mobile wireless applications. They also address challenges such as data management, scalability, regulations, interoperability, device network human interfaces, security, and privacy. Further study on these applications is required to ensure this technology is utilized appropriately. Multi-Disciplinary Applications of Fog Computing: Responsiveness in Real-Time focuses on fog computing problems and solutions for various applications and covers the new approaches, architecture, and theoretical foundations in the fog paradigm of storage, communication, and computing. The book explores recent trends and challenges that lead to a potential course for the ideas, practices, norms, and strategies related to fog computing. Covering key topics such as data privacy, data analytics, and the internet of things, this reference work is ideal for computer scientists, policymakers, researchers, scholars, practitioners, instructors, and students.
Book Synopsis Perspectives on Artificial Intelligence in Times of Turbulence: Theoretical Background to Applications by : Geada, Nuno
Download or read book Perspectives on Artificial Intelligence in Times of Turbulence: Theoretical Background to Applications written by Geada, Nuno and published by IGI Global. This book was released on 2023-11-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perspectives on Artificial Intelligence in Times of Turbulence: Theoretical Background to Applications offers a comprehensive exploration of the intricate relationship between artificial intelligence (AI) and the ever-changing landscape of our society. The book defines AI as machines capable of performing tasks that were once exclusive to human cognition. However, it emphasizes the current limitations of AI, dispelling the notion of sophisticated cyborgs depicted in popular culture. These machines lack self-awareness, struggle with understanding context—especially in language—and are constrained by historical data and predefined parameters. This distinction sets the stage for examining AI's impact on the job market and the evolving roles of humans and machines. Rather than portraying AI as a threat, this book highlights the symbiotic relationship between humans and machines. It recognizes that while certain jobs may become obsolete, new opportunities will emerge. The unique abilities of human beings—such as relational skills, emotional intelligence, adaptability, and understanding of differences—will continue to be indispensable in a rapidly transforming society. Its perspectives cover a wide range of topics such as business sustainability, change management, cybersecurity, digital economy and transformation, information systems management, management models and tools, and continuous improvement are comprehensively addressed. Additionally, the book delves into healthcare, telemedicine, Health 4.0, privacy and security, knowledge management, learning, and presents real-world case studies. Designed for researchers and professionals seeking to enhance their knowledge and research capabilities, this book offers a consistent theoretical and practical foundation. It serves as a springboard for further studies, supports change management initiatives within organizations, and facilitates knowledge sharing among experts. This book is an essential companion for colleges with master's and Ph.D. degree investigators, and researchers across a wide range of disciplines.
Book Synopsis Application and Adoption of Robotic Process Automation for Smart Cities by : Tailor, R.K.
Download or read book Application and Adoption of Robotic Process Automation for Smart Cities written by Tailor, R.K. and published by IGI Global. This book was released on 2023-10-25 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the present era, technological developments are increasing the efficiency and potential of each stakeholder in a business. Robotic process automation is one of the key areas that can be applied in business organizations and corporate sectors to enhance productivity and show a path to success. Application and Adoption of Robotic Process Automation for Smart Cities provides relevant theoretical frameworks and various developments in the area of robotic process automation. Covering topics such as banking and financial services, public engagement, and smart cities, this premier reference source is a valuable resource for business leaders, IT managers, government officials, engineers, students and educators of higher education, researchers, and academicians.
Book Synopsis Handbook of Research on Thrust Technologies Effect on Image Processing by : Pandey, Binay Kumar
Download or read book Handbook of Research on Thrust Technologies Effect on Image Processing written by Pandey, Binay Kumar and published by IGI Global. This book was released on 2023-08-04 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing integrates and extracts data from photos for a variety of uses. Applications for image processing are useful in many different disciplines. A few examples include remote sensing, space applications, industrial applications, medical imaging, and military applications. Imaging systems come in many different varieties, including those used for chemical, optical, thermal, medicinal, and molecular imaging. To extract the accurate picture values, scanning methods and statistical analysis must be used for image analysis. Thrust Technologies Effect on Image Processing provides insights into image processing and the technologies that can be used to enhance additional information within an image. The book is also a useful resource for researchers to grow their interest and understanding in the burgeoning fields of image processing. Covering key topics such as image augmentation, artificial intelligence, and cloud computing, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Book Synopsis Technological Tools for Predicting Pregnancy Complications by : Satishkumar, D.
Download or read book Technological Tools for Predicting Pregnancy Complications written by Satishkumar, D. and published by IGI Global. This book was released on 2023-10-09 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: The lack of comprehensive, innovative insights into the intricate world of pregnancy complication prediction is a pressing concern, as these complications can severely impact the health and wellbeing of pregnant patients. As the complexities of maternal healthcare continue to evolve, scholars grapple with the challenge of staying at the forefront of research and innovation in this critical field. The unpredictability of pregnancy complications poses significant risks to positive patient outcomes, demanding novel approaches to diagnosis and prevention. The academic community seeks a solution that can bridge the gap between traditional research and the transformative potential of technological advancements in healthcare. Technological Tools for Predicting Pregnancy Complications not only identify the problem but offer an authoritative solution. It serves as a beacon of knowledge for academic scholars, providing a holistic exploration of how Artificial Intelligence (AI) and Machine Learning (ML) technologies can revolutionize maternal healthcare. With a laser focus on predictive models, comprehensive health data analysis, and innovative algorithmic approaches, this book equips scholars with the tools they need to navigate the ever-evolving landscape of pregnancy complications. Academic scholars will find a treasure trove of insights, spanning from the fundamentals of AI and ML in healthcare to the application of IoT devices and wearable sensors for expectant mothers.
Download or read book Python written by Sebastian Raschka and published by . This book was released on 2017-06-29 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Machine Learning with Python by : Andreas C. Müller
Download or read book Introduction to Machine Learning with Python written by Andreas C. Müller and published by "O'Reilly Media, Inc.". This book was released on 2016-09-26 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
Book Synopsis Machine Learning by : Jason Callaway
Download or read book Machine Learning written by Jason Callaway and published by . This book was released on 2020-03-08 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you searching for the fastest way to discover the secrets of the fascinating world of Computer Science? For a very limited time, you have the opportunity to get three best-selling guides in a single phenomenal mega bundle: if you are a student or a professional looking for more technical skills, then this is definitely the book for you. In this complete crash course Jason Callaway has condensed all the knowledge you need in a clear and beginner-friendly way, with practical examples, detailed explanations, tips and tricks from his experience. His revolutionary approach will speed up your learning, allowing you to master the Python language and its powerful applications for Machine Learning in an extremely short time, even if you are a complete beginner. Here is just a tiny fraction of what you will learn: The basics of Python programming variables, data types, basic and advanced operations Essential Python libraries such as NumPy, Pandas, Matplotlib The most up-to-date computational methods and visualization techniques for data science Real-world applications of machine learning and artificial intelligence How to build statistical and machine learning models Neural networks and predictive modeling The OSI reference model Computer Network Communication systems and their applications Wireless technologies and their vulnerabilities If you are ready to develop a successful career in the growing industry of computer science, then click the BUY button and get your copy!
Book Synopsis Machine Learning by : Jason Callaway
Download or read book Machine Learning written by Jason Callaway and published by . This book was released on 2020-08-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you searching for the fastest way to discover the secrets of the fascinating world of Computer Science? Today you have the opportunity to get three best-selling guides in a single phenomenal mega bundle: if you are a student or a professional looking for more technical skills, then this is definitely the book for you. In this complete crash course Jason Callaway has condensed all the knowledge you need in a clear and beginner-friendly way, with practical examples, detailed explanations, tips and tricks from his experience. His revolutionary approach will speed up your learning, allowing you to master the Python language and its powerful applications for Machine Learning in an extremely short time, even if you are a complete beginner. Here is just a tiny fraction of what you will learn: The basics of Python programming variables, data types, basic and advanced operations Essential Python libraries such as NumPy, Pandas, Matplotlib The most up-to-date computational methods and visualization techniques for data science Real-world applications of machine learning and artificial intelligence How to build statistical and machine learning models Neural networks and predictive modeling The OSI reference model Computer Network Communication systems and their applications Wireless technologies and their vulnerabilities If you are ready to develop a successful career in the growing industry of computer science, then click the BUY button and get your copy!
Book Synopsis Machine Learning by : Jason Callaway
Download or read book Machine Learning written by Jason Callaway and published by . This book was released on 2020-08-25 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you searching for the fastest way to discover the secrets of the fascinating world of Computer Science? Today you have the opportunity to get three best-selling guides in a single phenomenal mega bundle: if you are a student or a professional looking for more technical skills, then this is definitely the book for you. In this complete crash course Jason Callaway has condensed all the knowledge you need in a clear and beginner-friendly way, with practical examples, detailed explanations, tips and tricks from his experience. His revolutionary approach will speed up your learning, allowing you to master the Python language and its powerful applications for Machine Learning in an extremely short time, even if you are a complete beginner. Here is just a tiny fraction of what you will learn: The basics of Python programming variables, data types, basic and advanced operations Essential Python libraries such as NumPy, Pandas, Matplotlib The most up-to-date computational methods and visualization techniques for data science Real-world applications of machine learning and artificial intelligence How to build statistical and machine learning models Neural networks and predictive modeling The OSI reference model Computer Network Communication systems and their applications Wireless technologies and their vulnerabilities If you are ready to develop a successful career in the growing industry of computer science, then click the BUY button and get your copy!
Book Synopsis Advanced Machine Learning with Python by : John Hearty
Download or read book Advanced Machine Learning with Python written by John Hearty and published by Packt Publishing Ltd. This book was released on 2016-07-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book Resolve complex machine learning problems and explore deep learning Learn to use Python code for implementing a range of machine learning algorithms and techniques A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Apply your new found skills to solve real problems, through clearly-explained code for every technique and test Automate large sets of complex data and overcome time-consuming practical challenges Improve the accuracy of models and your existing input data using powerful feature engineering techniques Use multiple learning techniques together to improve the consistency of results Understand the hidden structure of datasets using a range of unsupervised techniques Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.
Book Synopsis Advanced Deep Learning with Python by : Ivan Vasilev
Download or read book Advanced Deep Learning with Python written by Ivan Vasilev and published by Packt Publishing Ltd. This book was released on 2019-12-12 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem Key FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook Description In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN models. In this book, you’ll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You’ll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you’ll focus on variational autoencoders and GANs. You’ll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You’ll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you’ll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you’ll understand how to apply deep learning to autonomous vehicles. By the end of this book, you’ll have mastered key deep learning concepts and the different applications of deep learning models in the real world. What you will learnCover advanced and state-of-the-art neural network architecturesUnderstand the theory and math behind neural networksTrain DNNs and apply them to modern deep learning problemsUse CNNs for object detection and image segmentationImplement generative adversarial networks (GANs) and variational autoencoders to generate new imagesSolve natural language processing (NLP) tasks, such as machine translation, using sequence-to-sequence modelsUnderstand DL techniques, such as meta-learning and graph neural networksWho this book is for This book is for data scientists, deep learning engineers and researchers, and AI developers who want to further their knowledge of deep learning and build innovative and unique deep learning projects. Anyone looking to get to grips with advanced use cases and methodologies adopted in the deep learning domain using real-world examples will also find this book useful. Basic understanding of deep learning concepts and working knowledge of the Python programming language is assumed.
