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Low Code Practical Project Driven Introduction by Stripling Gwendolyn (12 results)
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Paperback. Condition: Fair. No Jacket. Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
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Low-Code AI : A Practical Project-Driven Introduction to Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 59.76
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Low-Code AI: A Practical Project-Driven Introduction to Machine Learning
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 67.16
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Low-Code AI: A Practical Project-Driven Introduction to Machine Learning (Paperback or Softback)
Language: English
Published by O'Reilly Media 10/17/2023, 2023
ISBN 10: 1098146824 ISBN 13: 9781098146825
Paperback or Softback. Condition: New. Low-Code AI: A Practical Project-Driven Introduction to Machine Learning. Book.
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Low-Code AI : A Practical Project-Driven Introduction to Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 70.43
US$ 20.25 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Low-code Ai: A Practical Project-driven Introduction to Machine Learning
Language: English
Published by Oreilly & Associates Inc, 2023
ISBN 10: 1098146824 ISBN 13: 9781098146825
US$ 90.53
US$ 16.87 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 350 pages. 9.19x7.00x0.69 inches. In Stock.
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Paperback. Condition: Neu. Neu Neuware, Importqualität, auf Lager - 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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Low-code Ai: A Practical Project-driven Introduction to Machine Learning
Language: English
Published by Oreilly & Associates Inc, 2023
ISBN 10: 1098146824 ISBN 13: 9781098146825
US$ 84.43
US$ 16.87 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 350 pages. 9.19x7.00x0.69 inches. In Stock. This item is printed on demand.
