Practical Solutions for Data-Driven Systems and Intelligent Automation with Python
This fourth volume in the Python in Practice series expands the skills of experienced developers into the domains of data science, machine learning, workflow automation, and embedded systems. Building upon the foundational topics introduced in earlier volumes, this book offers hands-on insights into the modern tools and techniques required for data-intensive applications.
From exploratory data analysis with Pandas and Jupyter to machine learning workflows using Scikit-learn and PyTorch, and from intelligent process automation with APIs and web scraping to IoT control and scalable ETL pipelines-each chapter addresses real-world challenges with practical Python solutions.
Exploratory data analysis, time series modeling, and visualization
Classical and deep learning with PyTorch and Scikit-learn
Automation of files, formats, APIs, and emails
IoT integration and sensor-actuator control
Efficient ETL pipelines and high-performance computing with Dask and Numba
Designed for developers, analysts, and engineers who aim to apply Python beyond scripts-toward scalable, intelligent systems.