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 by Jonathan Norman
English | June 3, 2025 | ISBN: N/A | ASIN: B0FBWL5C5F | 585 pages | EPUB | 0.28 Mb
English | June 3, 2025 | ISBN: N/A | ASIN: B0FBWL5C5F | 585 pages | EPUB | 0.28 Mb
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
- 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
If you’re ready to build solutions—not just models—this is the book that will get you there.