Automated Machine Learning in Action PDF Download – Qingquan Song, Haifeng Jin
Automated Machine Learning in Action Summary and Overview
Building high-quality machine learning models normally requires weeks of manual tuning, feature engineering, and validation effort. In Automated Machine Learning in Action PDF, authors Qingquan Song and Haifeng Jin present a modern approach to optimizing the model development process itself. This technical book serves as a vital resource for data scientists and software engineers looking to implement AutoML tools that accelerate delivery speed without sacrificing accuracy.
The text details how to leverage automated search algorithms, neural architecture search, and hyperparameter optimization to create production-ready models from scratch. It explains how to build pipelines that automatically clean datasets, select the most relevant features, and compare multiple algorithmic learners concurrently. Each section provides clean, modular code examples that highlight how to apply these automation techniques within standard Python data science environments.
Utilizing this comprehensive manual allows analytics teams to increase their project throughput and focus on high-level business logic rather than tedious manual model tweaking. It bridges the gap between theoretical research into auto-tuning and the practical realities of industrial data deployments. For any developer looking to master automated pipeline construction, this digital textbook offers a highly detailed architectural framework.
PDF Book Details and Analysis
| 📖 Book Title: | Automated Machine Learning in Action |
| ✍️ Author: | Qingquan Song, Haifeng Jin |
| 📁 Category: | Data Science, Machine Learning, Automation, Programming, English |
| 🌍 Language: | English |
| 📄 File Type: |
click here to join our channel.
Follow us on Telegram: