Deep Learning In Modern C
DOWNLOAD
Download Deep Learning In Modern C PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Learning In Modern C book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Deep Learning In Modern C
DOWNLOAD
Author : Luiz Carlos d’Oleron
language : en
Publisher: BPB Publications
Release Date : 2025-04-23
Deep Learning In Modern C written by Luiz Carlos d’Oleron and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-23 with Computers categories.
DESCRIPTION Deep learning is revolutionizing how we approach complex problems, and harnessing its power directly within C++ provides unparalleled control and efficiency. This book bridges the gap between cutting-edge deep learning techniques and the robust, high-performance capabilities of modern C++, empowering developers to build sophisticated AI applications from the ground up. This book guides you through the entire development lifecycle, starting with a solid foundation in the modern features and essential libraries, like Eigen, for C++. You will master core deep learning concepts by implementing convolutions, fully connected layers, and activation functions, while learning to optimize models using gradient descent, backpropagation, and advanced optimizers like SGD, Momentum, RMSProp, and Adam. Crucial topics like cross-validation, regularization, and performance evaluation are covered, ensuring robust and reliable applications. Finally, you will dive into computer vision, building image classifiers and object localization systems, leveraging transfer learning for optimal performance. By the end of this book, you will be proficient in developing and deploying deep learning models within C++, equipped with the tools and knowledge to tackle real-world AI challenges with confidence and precision. WHAT YOU WILL LEARN ● Implement core deep learning models in modern C++. ● Code CNNs, RNNs, GANs, and optimization techniques. ● Build and test robust deep learning C++ applications. ● Apply transfer learning in C++ computer vision tasks. ● Master backpropagation and gradient descent in C++. ● Develop image classifiers and object detectors in C++. WHO THIS BOOK IS FOR This book is tailored for C++ developers, data scientists, and machine learning engineers seeking to implement deep learning models using modern C++. A foundational understanding of C++ programming and basic linear algebra is recommended. TABLE OF CONTENTS 1. Introduction to Deep Learning Programming 2. Coding Deep Learning with Modern C++ 3. Testing Deep Learning Code 4. Implementing Convolutions 5. Coding the Fully Connected Layer 6. Learning by Minimizing Cost Functions 7. Defining Activation Functions 8. Using Pooling Layers 9. Coding the Gradient Descent Algorithm 10. Coding the Backpropagation Algorithm 11. Underfitting, Overfitting, and Regularization 12. Implementing Cross-validation, Mini Batching, and Model Performance Metrics 13. Implementing Optimizers 14. Introducing Computer Vision Models 15. Developing an Image Classifier 16. Leveraging Training Performance with Transfer Learning 17. Developing an Object Localization System
Design Patterns In Modern C
DOWNLOAD
Author : Dmitri Nesteruk
language : en
Publisher: Apress
Release Date : 2018-04-18
Design Patterns In Modern C written by Dmitri Nesteruk and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-18 with Computers categories.
Apply modern C++17 to the implementations of classic design patterns. As well as covering traditional design patterns, this book fleshes out new patterns and approaches that will be useful to C++ developers. The author presents concepts as a fun investigation of how problems can be solved in different ways, along the way using varying degrees of technical sophistication and explaining different sorts of trade-offs. Design Patterns in Modern C++ also provides a technology demo for modern C++, showcasing how some of its latest features (e.g., coroutines) make difficult problems a lot easier to solve. The examples in this book are all suitable for putting into production, with only a few simplifications made in order to aid readability. What You Will Learn Apply design patterns to modern C++ programming Use creational patterns of builder, factories, prototype and singleton Implement structural patterns such as adapter, bridge, decorator, facade and more Work with the behavioral patterns such as chain of responsibility, command, iterator, mediator and more Apply functional design patterns such as Monad and more Who This Book Is For Those with at least some prior programming experience, especially in C++.
Deep Learning With Pytorch
DOWNLOAD
Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2023-03-21
Deep Learning With Pytorch written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
Deep learning is currently the most interesting and powerful machine learning technique. PyTorch is one of the dominant libraries for deep learning in the Python ecosystem and is widely used in research. With PyTorch, you can easily tap into the power of deep learning with just a few lines of code. Many deep learning models are created in PyTorch. Therefore, knowing PyTorch opens the door for you to leverage the power of deep learning. This Ebook is written in the friendly Machine Learning Mastery style that you’re used to, learn exactly how to get started and apply deep learning to your own machine learning projects.
Hands On Machine Learning With C
DOWNLOAD
Author : Kirill Kolodiazhnyi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-01-24
Hands On Machine Learning With C written by Kirill Kolodiazhnyi 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 2025-01-24 with Computers categories.
Apply supervised and unsupervised machine learning algorithms using C++ libraries, such as PyTorch C++ API, Flashlight, Blaze, mlpack, and dlib using real-world examples and datasets Key Features Familiarize yourself with data processing, performance measuring, and model selection using various C++ libraries Implement practical machine learning and deep learning techniques to build smart models Deploy machine learning models to work on mobile and embedded devices Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by a seasoned software engineer with several years of industry experience, this book will teach you the basics of machine learning (ML) and show you how to use C++ libraries, along with helping you create supervised and unsupervised ML models. You’ll gain hands-on experience in tuning and optimizing a model for various use cases, enabling you to efficiently select models and measure performance. The chapters cover techniques such as product recommendations, ensemble learning, anomaly detection, sentiment analysis, and object recognition using modern C++ libraries. You’ll also learn how to overcome production and deployment challenges on mobile platforms, and see how the ONNX model format can help you accomplish these tasks. This new edition has been updated with key topics such as sentiment analysis implementation using transfer learning and transformer-based models, as well as tracking and visualizing ML experiments with MLflow. An additional section shows you how to use Optuna for hyperparameter selection. The section on model deployment into mobile platform now includes a detailed explanation of real-time object detection for Android with C++. By the end of this C++ book, you’ll have real-world machine learning and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.What you will learn Employ key machine learning algorithms using various C++ libraries Load and pre-process different data types to suitable C++ data structures Find out how to identify the best parameters for a machine learning model Use anomaly detection for filtering user data Apply collaborative filtering to manage dynamic user preferences Utilize C++ libraries and APIs to manage model structures and parameters Implement C++ code for object detection using a modern neural network Who this book is for This book is for beginners looking to explore machine learning algorithms and techniques using C++. This book is also valuable for data analysts, scientists, and developers who want to implement machine learning models in production. Working knowledge of C++ is needed to make the most of this book.
Deep Learning And Parallel Computing Environment For Bioengineering Systems
DOWNLOAD
Author : Arun Kumar Sangaiah
language : en
Publisher: Academic Press
Release Date : 2019-07-26
Deep Learning And Parallel Computing Environment For Bioengineering Systems written by Arun Kumar Sangaiah and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-26 with Technology & Engineering categories.
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. - Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems - Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems - Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data
Current Trends And Approaches In The Comprehensive Evaluation Of Coronary Artery Disease
DOWNLOAD
Author : Dobrin Vassilev
language : en
Publisher: Frontiers Media SA
Release Date : 2023-11-13
Current Trends And Approaches In The Comprehensive Evaluation Of Coronary Artery Disease written by Dobrin Vassilev and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-13 with Medical categories.
Coronary Artery Disease (CAD) is a global health concern with high prevalence, morbidity and mortality rate. This Editorial initiative is focused on the current diagnostic approaches in the comprehensive assessment of CAD including anatomic and functional evaluation of the whole coronary circulation. Authors are encouraged to focus on the latest advancements in research across the field of invasive and non-invasive methods for evaluation of epicardial CAD and coronary microvascular disease. To address the growing population of CAD patients, new diagnostic methods and approaches are being investigated in order to achieve better clinical outcomes and symptom alleviation in this population. The goal of this Research topic is to offer a broad overview of the current diagnostic methods, to shed light on the unmet clinical needs and provide directions for new research topics.
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough
DOWNLOAD
Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2021-04-26
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-26 with Technology & Engineering categories.
This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
Python Machine Learning Cookbook
DOWNLOAD
Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-30
Python Machine Learning Cookbook written by Giuseppe Ciaburro 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 2019-03-30 with Computers categories.
Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key FeaturesLearn and implement machine learning algorithms in a variety of real-life scenariosCover a range of tasks catering to supervised, unsupervised and reinforcement learning techniquesFind easy-to-follow code solutions for tackling common and not-so-common challengesBook Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learnUse predictive modeling and apply it to real-world problemsExplore data visualization techniques to interact with your dataLearn how to build a recommendation engineUnderstand how to interact with text data and build models to analyze itWork with speech data and recognize spoken words using Hidden Markov ModelsGet well versed with reinforcement learning, automated ML, and transfer learningWork with image data and build systems for image recognition and biometric face recognitionUse deep neural networks to build an optical character recognition systemWho this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.
Machine Learning Proceedings 1994
DOWNLOAD
Author : William W. Cohen
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-06-28
Machine Learning Proceedings 1994 written by William W. Cohen and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
Machine Learning Proceedings 1994
Contemporary Medicine Making Sense Of Implementation Models And Methods
DOWNLOAD
Author : Michele Mario Ciulla
language : en
Publisher: Frontiers Media SA
Release Date : 2022-06-01
Contemporary Medicine Making Sense Of Implementation Models And Methods written by Michele Mario Ciulla and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Medical categories.