Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Low-Code AI: A Practical Project-Driven Introduction to Machine Learning

Low-Code AI: A Practical Project-Driven Introduction to Machine Learning

Abel, Michael
Stripling, Gwendolyn
Dillard, Stephanie

Audio Book

ApplicationsGeneral Computers

Currently unavailable to order

ISBN13: 9798228679450
Publisher: Ascent Audio
Published: Sep 30 2025
Language: English
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; and export data to a GitHub repository for data management and governance.

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