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OverviewTake 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. Full Product DetailsAuthor: Michael Abel , Gwendolyn Stripling , Stephanie DillardPublisher: Ascent Audio Imprint: Ascent Audio Edition: Unabridged edition ISBN: 9798228679450Publication Date: 30 September 2025 Audience: General/trade , General Format: Audio Publisher's Status: Active Availability: In Print This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationGwendolyn Stripling, PhD, is an artificial intelligence and machine learning content developer at Google Cloud, helping learners navigate their generative AI and AI/ML journey. Stripling is the creator of the successful YouTube video ""Introduction to Generative AI"". Gwendolyn is also the author of the LinkedIn Learning course Artificial Intelligence Foundations: Neural Networks (released 9/18/2023) and Advanced NLP with Python for Machine Learning (2024). Stephanie Dillard holds a Master of Music degree from Westminster Choir College in Princeton, New Jersey, where she trained formally as an opera singer and choral conductor. However, her heart has always been in the world of theater, which is why she began narrating audiobooks from her studio in Tennessee. While she remains active in the world of live theater and music education, Stephanie now brings those talents to bear behind the mic to give a wide range of vocal colors and emotional nuance to her characters. When not in the booth, she can be found gardening, hiking, and camping with her husband and two young sons. Tab Content 6Author Website:Countries AvailableAll regions |
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