VOLUME 13 – Artificial Intelligence & Data Science Artificial Intelligence Introduction to Machine Learning Machine Learning Applied Artificial Intelligence Neural Networks and Deep Learning AI in Engineering and Industry

VOLUME 13: Artificial Intelligence & Data Science

Series: Manuals for Students

Publisher: GK Edition

Overview

Designed for data scientists, artificial intelligence researchers, and engineering professionals, Volume 13 of the Manuals for Students series delivers an exhaustive and structured exploration of modern machine learning, deep neural architectures, and intelligent systems. This volume bridges theoretical foundations with cutting-edge industrial implementations, equipping readers with the advanced mathematical and computational methodologies required to build autonomous, data-driven systems.

Key Modules Included:

1. Artificial Intelligence: Foundational principles of intelligent agents, symbolic reasoning, knowledge representation, search algorithms, and automated decision-making frameworks.
2. Introduction to Machine Learning: Core paradigms of supervised, unsupervised, and reinforcement learning, model evaluation, feature engineering, and validation techniques.
3. Machine Learning: Advanced algorithmic implementations, regression models, classification techniques, clustering, ensemble methods, and optimization algorithms.
4. Applied Artificial Intelligence: Practical integration of AI models into real-world software workflows, natural language processing foundations, and computer vision basics.
5. Neural Networks and Deep Learning: In-depth study of multi-layer perceptrons, convolutional neural networks (CNNs), recurrent networks (RNNs), and modern deep learning architectures.
6. AI in Engineering and Industry: Industrial deployment of AI systems, predictive maintenance, process automation, robotics integration, and smart manufacturing optimization.

Postscript: All deep-dive volumes are part of the academic series published by GK Edition.