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Low-Code AI converted Gwendolyn Stripling Phd; Michael Abel Phd

  • SKU: BELL-53569838
Low-Code AI converted Gwendolyn Stripling Phd; Michael Abel Phd
$ 31.00 $ 45.00 (-31%)

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Low-Code AI converted Gwendolyn Stripling Phd; Michael Abel Phd instant download after payment.

Publisher: O'Reilly Media
File Extension: PDF
File size: 16.85 MB
Author: Gwendolyn Stripling PhD; Michael Abel PhD
ISBN: 9781098146825, 1098146824
Language: English
Year: 2023
Edition: converted

Product desciption

Low-Code AI converted Gwendolyn Stripling Phd; Michael Abel Phd by Gwendolyn Stripling Phd; Michael Abel Phd 9781098146825, 1098146824 instant download after payment.

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 presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, 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 between structured and unstructured data and the 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 ML 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
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