Artificial Intelligence Essentials by Oliver Kramer (.ePUB)+
File Size: 14.0 MB
Artificial Intelligence Essentials by Oliver Kramer
Requirements: .ePUB, .PDF reader, 14.0 MB | True PDF, True EPUB
Overview: The book provides a structured introduction to core areas of Artificial Intelligence, including Machine Learning, Deep Learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as Scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive notebooks. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in Computer Science or related fields and can be used for teaching, self-study, or reference in applied contexts. Artificial Intelligence (AI) describes systems that learn, reason, and make decisions. Modern AI relies on Deep Learning and neural networks. These models handle tasks such as language processing, image recognition, and automated decision-making. Early AI used rule-based systems, but current progress comes from Machine Learning on large datasets. Large language models (LLMs) show recent advances. They use transformer networks to generate text, support programming, and solve reasoning tasks. Agentic AI extends these models. It connects LLMs with automation and performs multi-step tasks with minimal human input. AI systems now move from static behavior to adaptive and interactive operation. AI also operates beyond language. New methods create images, master complex games, and control robots. Research pushes AI into healthcare, finance, and scientific discovery. Its impact grows as it enters more domains. This book introduces Machine Learning with Scikit-learn, Keras, and LLMs via ollama. Each chapter provides practical examples in Python and exercises for real applications.
Genre: Non-Fiction > Tech & Devices
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