Low-Code AI: A Practical Project-Driven Introduction to Machine Learning. Gwendolyn Stripling, Michael Abel
Low-Code-AI-A-Practical-Project.pdf
ISBN: 9781098146825 | 350 pages | 9 Mb
- Low-Code AI: A Practical Project-Driven Introduction to Machine Learning
- Gwendolyn Stripling, Michael Abel
- Page: 350
- Format: pdf, ePub, fb2, mobi
- ISBN: 9781098146825
- Publisher: O'Reilly Media, Incorporated
Download free pdf ebook Low-Code AI: A Practical Project-Driven Introduction to Machine Learning
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. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data, feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish structured and unstructured data and understand the different challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different machine learning model types and architectures, from no code to low-code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance
Low-Code AI: A Practical Project-Driven Introduction to
Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide
The best-selling new & future releases in Machine Theory
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Low-Code AI by Gwendolyn Stripling, Michael Abel | eBook
Take a data-first and use-case–driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on.
Low-Code AI A Practical Project-Driven Introduction to
Low-Code AI A Practical Project-Driven Introduction to Machine Learning [Early Release ed.] 9781098146825, 9781098146764 · Take a data-first and use-case driven
Low-Code AI: A Practical Project-Driven Introduction to
Low-Code AI: A Practical Project-Driven Introduction to Machine Learning by Gwendolyn Stripling, Michael Abel, 325 pages, 2023-10-17. Read It Now.
A Practical Project-Driven Introduction to Machine Learning
Take a data-first and use-case-driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide present
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Low-Code AI: A Practical Project-Driven Introduction to Machine Learning. Low-Code AI: A Practical Project-Driven Introduction $59.36$79.99 (26% off).
The best-selling new & future releases in Machine Theory
Low-Code AI: A Practical Project-Driven Introduction to Machine Learning. 1 offer
Low-Code AI: A Practical Project-Driven Introduction to
Название: Low-Code AI: A Practical Project-Driven Introduction to Machine Learning (Early Release)Автор: Gwendolyn Stripling, Michael AbelИздательство:
Low-Code AI: A Practical Project-Driven Introduction to
Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and
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