Practical AI with Python: Build 10 Real-World Projects from Data to Deployment

Practical AI with Python
Build 10 Real-World Projects from Data to Deployment
Transform your Python skills into real-world AI solutions with this project-driven guide to applied artificial intelligence. Practical AI with Python is your gateway to mastering the end-to-end development of intelligent systems that make a measurable impact—from initial data preprocessing all the way to live deployment.
This hands-on book walks you through 10 comprehensive AI projects designed to mirror real industry demands. Whether you're developing a recommendation engine, building an image recognition model, or deploying NLP-powered chatbots, each project offers clear instructions, clean code, and professional insight into the tools and workflows used by today’s AI engineers.
What you’ll build:

• A customer churn prediction model that drives smarter retention strategies
• An AI-powered movie recommender for personalizing content
• A real-time sentiment analyzer that deciphers public opinion from text
• A document classifier using NLP and machine learning techniques
• A deep learning image recognizer with convolutional neural networks
• A chatbot with NLP pipelines and intent recognition
• An AI-powered spam detection engine using feature engineering
• A time series forecasting system for business and financial trends
• A Flask/FastAPI microservice for your deployed AI models
• A cloud-deployed AI pipeline with Docker, REST APIs, and CI/CD principles

Key features include:

• End-to-End Workflows: Learn the full AI pipeline—from data cleaning and model training to performance tuning and deployment
• Industry Tools & Libraries: Work with pandas, NumPy, scikit-learn, TensorFlow, Keras, OpenCV, spaCy, and more
• Deployment-Ready Code: Integrate your models into production environments using Flask, FastAPI, and Docker
• Real-World Challenges: Solve problems modeled after common use cases in marketing, customer service, logistics, and software development
• Best Practices: Understand model explainability, ethical considerations, data governance, and API security

Whether you're a developer aiming to break into AI, a data analyst looking to build practical skills, or a student preparing for a career in machine learning, this book gives you the foundation, confidence, and real experience to create AI that works in the real world.
If you’re ready to build solutions—not just models—this is the book that will get you there.