Advanced Applied Deep Learning
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Advanced Applied Deep Learning
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Author : Umberto Michelucci
language : en
Publisher: Apress
Release Date : 2019-09-28
Advanced Applied Deep Learning written by Umberto Michelucci and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-28 with Computers categories.
Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along the way, you will look at the fundamental operations in CNN, such as convolution and pooling, and then look at more advanced architectures such as inception networks, resnets, and many more. While the book discusses theoretical topics, you will discover how to work efficiently with Keras with many tricks and tips, including how to customize logging in Keras with custom callback classes, what is eager execution, and how to use it in your models. Finally, you will study how object detection works, and build a complete implementation of the YOLO (you only look once) algorithm in Keras and TensorFlow. By the end of the book you will have implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level. What You Will Learn See how convolutional neural networks and object detection work Save weights and models on disk Pause training and restart it at a later stage Use hardware acceleration (GPUs) in your code Work with the Dataset TensorFlow abstraction and use pre-trained models and transfer learning Remove and add layers to pre-trained networks to adapt them to your specific project Apply pre-trained models such as Alexnet and VGG16 to new datasets Who This Book Is For Scientists and researchers with intermediate-to-advanced Python and machine learning know-how. Additionally, intermediate knowledge of Keras and TensorFlow is expected.
Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning
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Author : Raygoza-L., Maria E.
language : en
Publisher: IGI Global
Release Date : 2025-03-06
Exploring Psychology Social Innovation And Advanced Applications Of Machine Learning written by Raygoza-L., Maria E. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.
Machine learning (ML algorithms can be used to better understand human behavior in its various developmental stages and to assist in addressing psychological issues. Additionally, in the realm of mental health and well-being, algorithms can assist with early detection of disorders and customization of treatments as well as personalize recommendations and suggestions based on user behavior. By focusing on user experience and usability, ML may be used to address challenges faced by private enterprises and social issues. Exploring Psychology, Social Innovation and Advanced Applications of Machine Learning explores the relationships between human psychology and machine learning technology, enabling researchers to delve into areas such as user interface design, ethics in artificial intelligence, and the social impact of algorithms. Furthermore, it promotes interdisciplinary collaboration by bringing together perspectives from different fields, which could stimulate new research and innovative approaches in the field of machine learning. Covering topics such as industrial processes, digital therapy, and machine vision, this book is an excellent resource for psychologists, computer scientists, engineers, healthcare practitioners, educators, business leaders, policymakers, professionals, researchers, scholars, academicians, and more.
Scala Applied Machine Learning
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Author : Pascal Bugnion
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-02-23
Scala Applied Machine Learning written by Pascal Bugnion and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-23 with Computers categories.
Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest features About This Book Build functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples provided Leverage your expertise in Scala programming to create and customize your own scalable machine learning algorithms Experiment with different techniques; evaluate their benefits and limitations using real-world financial applications Get to know the best practices to incorporate new Big Data machine learning in your data-driven enterprise and gain future scalability and maintainability Who This Book Is For This Learning Path is for engineers and scientists who are familiar with Scala and want to learn how to create, validate, and apply machine learning algorithms. It will also benefit software developers with a background in Scala programming who want to apply machine learning. What You Will Learn Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to perform technical analysis of financial markets Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions. The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial. The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Scala for Data Science, Pascal Bugnion Scala for Machine Learning, Patrick Nicolas Mastering Scala Machine Learning, Alex Kozlov Style and approach A tutorial with complete examples, this course will give you the tools to start building useful data engineering and data science solutions straightaway. This course provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.
Medicon 23 And Cmbebih 23
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Author : Almir Badnjević
language : en
Publisher: Springer Nature
Release Date : 2024-01-03
Medicon 23 And Cmbebih 23 written by Almir Badnjević and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-03 with Technology & Engineering categories.
This book presents cutting-edge research and developments in the broad field of medical, biological engineering and computing. It gathers the second volume of the joint proceedings of the Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON) and the International Conference on Medical and Biological Engineering (CMBEBIH), which were held together on September 14-16, 2023, in Sarajevo, Bosnia and Herzegovina. Contributions report on innovative research and practices in molecular biology, tissue engineering and biotechnologies, covering not only medical but also industrial applications. Further, they describe advances in health technologies and medical devices, telemedicine, and robotic applications in clinical medicine and rehabilitation.
Applied Deep Learning And Computer Vision For Self Driving Cars
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Author : Sumit Ranjan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-14
Applied Deep Learning And Computer Vision For Self Driving Cars written by Sumit Ranjan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Computers categories.
Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.
Applied Deep Learning With Tensorflow 2
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Author : Umberto Michelucci
language : en
Publisher: Apress
Release Date : 2022-04-18
Applied Deep Learning With Tensorflow 2 written by Umberto Michelucci and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-18 with Computers categories.
Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be opened directly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally. You will: • Understand the fundamental concepts of how neural networks work • Learn the fundamental ideas behind autoencoders and generative adversarial networks • Be able to try all the examples with complete code examples that you can expand for your own projects • Have available a complete online companion book with examples and tutorials. This book is for: Readers with an intermediate understanding of machine learning, linear algebra, calculus, and basic Python programming.
International Research In Engineering Sciences X
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Author : Servet Soygüder
language : en
Publisher: EĞİTİM YAYINEVİ
Release Date : 2024-08-02
International Research In Engineering Sciences X written by Servet Soygüder and has been published by EĞİTİM YAYINEVİ this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-02 with Business & Economics categories.
Generative Ai And Implications For Ethics Security And Data Management
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Author : Gomathi Sankar, Jeganathan
language : en
Publisher: IGI Global
Release Date : 2024-08-21
Generative Ai And Implications For Ethics Security And Data Management written by Gomathi Sankar, Jeganathan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-21 with Computers categories.
As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
Applied Machine Learning And Ai For Engineers
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Author : Jeff Prosise
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-11-10
Applied Machine Learning And Ai For Engineers written by Jeff Prosise and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Computers categories.
While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company. Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equations—just a fast start for engineers and software developers, complete with hands-on examples. This book helps you: Learn what machine learning and deep learning are and what they can accomplish Understand how popular learning algorithms work and when to apply them Build machine learning models in Python with Scikit-Learn, and neural networks with Keras and TensorFlow Train and score regression models and binary and multiclass classification models Build facial recognition models and object detection models Build language models that respond to natural-language queries and translate text to other languages Use Cognitive Services to infuse AI into the apps that you write
Algorithms In Advanced Artificial Intelligence
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Author : R. N. V. Jagan Mohan
language : en
Publisher: CRC Press
Release Date : 2025-05-23
Algorithms In Advanced Artificial Intelligence written by R. N. V. Jagan Mohan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.
Algorithms in Advanced Artificial Intelligence is a collection of papers on emerging issues, challenges, and new methods in Artificial Intelligence, Machine Learning, Deep Learning, Cloud Computing, Federated Learning, Internet of Things, and Blockchain technology. It addresses the growing attention to advanced technologies due to their ability to provide “paranormal solutions” to problems associated with classical Artificial Intelligence frameworks. AI is used in various subfields, including learning, perception, and financial decisions. It uses four strategies: Thinking Humanly, Thinking Rationally, Acting Humanly, and Acting Rationally. The authors address various issues in ICT, including Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Big Data Analytics, Vision, Internet of Things, Security and Privacy aspects in AI, and Blockchain and Digital Twin Integrated Applications in AI.