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Book synopsis

Python for Artificial Intelligence and Machine Learning is a practical, hands-on guide designed to help readers understand and build real-world AI systems using Python.

This book takes you from the fundamentals of Artificial Intelligence and Python programming to advanced topics such as machine learning, deep learning, natural language processing, and computer vision. Each concept is explained in a clear and structured way, making it suitable for both beginners and intermediate learners.

Rather than focusing only on theory, this book emphasizes practical learning. You will work with powerful tools such as NumPy, Pandas, Scikit-Learn, TensorFlow, and PyTorch to analyze data, build models, and solve real-world problems.

Inside the book, you will learn how to:

• Understand the core concepts of Artificial Intelligence and Machine Learning

• Write Python code for data analysis and AI development

• Build regression and classification models

• Apply clustering techniques for data insights

• Develop deep learning models using neural networks

• Work with natural language processing for text analysis

• Build computer vision systems for image recognition

• Deploy machine learning models using APIs

The book also includes real-world projects that help you apply your knowledge, including:

• Spam Email Detection

• House Price Prediction

• Customer Segmentation

• Image Recognition System

• Sentiment Analysis System

Whether you are a student, developer, or aspiring data scientist, this book provides a step-by-step roadmap to mastering Artificial Intelligence with Python.

By the end of this book, you will have the skills and confidence to design, build, and deploy intelligent systems that solve real-world problems.

Book details

• Full title: Python for Artificial Intelligence and Machine Learning
• Subtitle: A Practical Guide with Real-World Projects in Machine Learning, Deep Learning, NLP, Computer Vision, and AI Deployment
• Author: John Wang
• Language: English
• Binding: Paperback
• Number of pages: 280
• EAN: 9798252646893
• ID: 51515442
• Publisher: Independently published
• Weight: 487 g
• Dimensions: 235 × 191 × 15 mm
• Date of publishing: 18. March 2026

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