Description: Low-Code AI by Gwendolyne Stripling, Michael Abel 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. Youll learn key ML concepts by using real-world datasets with realistic problems. FORMAT Paperback CONDITION Brand New Publisher Description 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. Youll 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. Youll 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" Author Biography Michael Abel, PhD, is the technical lead for the specialized training program at Google Cloud, working to accelerate and deepen Cloud proficiency of customers through differentiated and non-standard learning experiences. Formerly, Abel was a data and machine learning technical trainer at Google Cloud and has taught the following Google Cloud courses: "Machine Learning on Google Cloud," "Advanced Solutions Labs ML Immersion," and "Data Engineering on Google Cloud." Before joining Google, Abel served as a Visiting Assistant Professor of Mathematics at Duke University, where he performed mathematics research and taught undergraduate mathematics. Michael Abel is the technical lead for the specialized training program at Google Cloud, working to accelerate and deepen Cloud proficiency of customers through differentiated and non-standard learning experiences. Formerly, Abel was a data and machine learning technical trainer at Google Cloud and has taught the following Google Cloud courses: Machine Learning on Google Cloud, Advanced Solutions Labs ML Immersion, and Data Engineering on Google Cloud. Before joining Google, Abel served as a Visiting Assistant Professor of Mathematics at Duke University, where he performed mathematics research and taught undergraduate mathematics. Details ISBN1098146824 Author Michael Abel Publisher OReilly Media Year 2023 ISBN-13 9781098146825 Format Paperback Imprint OReilly Media Subtitle A Practical Project-Driven Introduction to Machine Learning Place of Publication Sebastopol Country of Publication United States AU Release Date 2023-10-31 NZ Release Date 2023-10-31 UK Release Date 2023-10-31 ISBN-10 1098146824 Pages 325 Publication Date 2023-09-29 US Release Date 2023-09-29 DEWEY 006.31 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159081511;
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ISBN-13: 9781098146825
Author: Gwendolyne Stripling, Michael Abel
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Book Title: Low-Code AI
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