Machine Learning Automation with TPOT
Build, validate, and deploy fully automated machine learning models with Python
Created by Dario Radečić
Discover how to automate machine learning tasks using TPOT in Python. Learn to build, validate, and deploy high-performing models for both regression and classification without getting bogged down in complex manual processes. Gain practical skills that help you deliver production-ready solutions faster.
Packt | May 2021 | 270 min
What You Will Learn
You will follow clear, step-by-step explanations and work through practical examples using Python. Each section guides you through building and evaluating automated models, comparing them to traditional approaches, and deploying them in real-world scenarios. The focus is on hands-on practice to ensure you can apply these techniques confidently.
Key Features
- Automate the creation and optimization of machine learning pipelines with TPOT
- Build and compare classification and regression models using real-world datasets
- Deploy robust models in Python applications for immediate, practical use
Target Audience
Ideal for data scientists, analysts, and developers with basic Python and introductory machine learning knowledge. If you want to automate model building and deployment or streamline machine learning workflows in your projects, this course will help you achieve those goals efficiently.
