SKU/Artículo: AMZ-B0G2H46RDH
Machine Learning with C++: Practical Implementation of AI and ML Algorithms in C++
Format:
Kindle
Detalles del producto
Disponibilidad:
Fuera de stock
Fuera de stock
Peso con empaque:
0.15 kg
0.15 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Machine Learning with C++Practical Implementation of AI and ML Algorithms in C++.Unlock the true power of Artificial Intelligence by mastering Machine Learning with C++— the world’s fastest, most efficient, and production-ready programming language for AI applications.In this comprehensive, beginner-friendly yet deeply technical guide, you’ll learn how to design, implement, and optimize powerful machine learning algorithms in modern C++ (C++17/20/23). Whether you’re a data scientist looking to boost model performance, a C++ developer entering the AI field, or a researcher building high-speed intelligent systems, this book gives you the practical foundation you need to succeed.You’ll move step-by-step from the mathematical and statistical basics to building complete machine learning models, neural networks, and AI systems—all coded natively in C++ for speed, control, and efficiency. Every chapter includes hands-on coding examples, real-world projects, detailed explanations, and fully commented programs to help you learn by doing.Discover how to use C++ libraries like Eigen, Armadillo, Dlib, mlpack, and OpenCV to build everything from regression models and decision trees to deep learning architectures and reinforcement learning agents. Learn how to handle data, train models, optimize performance, and deploy machine learning solutions that scale.By the end of this book, you will not only understand the core algorithms behind AI and ML, but also know how to build, train, and deploy them efficiently using the full power of C++. What You’ll Learn Inside:Set up your C++ environment for AI and machine learning developmentImplement linear and logistic regression, decision trees, and ensemble models from scratchExplore unsupervised learning with K-Means, PCA, and clustering algorithmsBuild and train neural networks using C++ and integrate TensorFlow or DlibDevelop reinforcement learning agents and intelligent systemsPerform NLP tasks like text classification and sentiment analysisApply GPU acceleration with CUDA for deep learning performanceDeploy machine learning models into real-world C++ applications Perfect For:C++ programmers exploring Artificial Intelligence and Machine LearningSoftware engineers seeking high-performance model implementationsData scientists wanting to move beyond Python and gain low-level controlStudents, educators, and researchers in AI, computer science, and data engineeringDevelopers working on robotics, IoT, finance, or embedded AI applications Why This Book Stands Out:Unlike most AI and ML books that rely on Python, this guide focuses on hands-on implementation in C++, where performance truly matters. You’ll not only understand how machine learning works but also learn how to engineer it efficiently for large-scale, high-speed applications.
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