Low-Code AI: A Practical Project-Driven Introduction to Machine Learning (Early Release)
English | 2023 | ISBN: 9781098146818 | 109 pages | MOBI | 2.23 Mb
English | 2023 | ISBN: 9781098146818 | 109 pages | MOBI | 2.23 Mb
Take a data-first and use-case driven approach to understanding machine learning and deep learning concepts with Low-Code AI. This hands-on guide presents three problem-focused ways to learn ML: no code using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. You'll learn key ML concepts by using real-world datasets with realistic problems.
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