Description: Title: Low-Code AI: A Practical Project-Driven Introduction to Machine Learning Author: Stripling, Gwendolyn Publisher: O'Reilly Media Inc. Binding: Paperback Pages: 325 Dimensions: 9.19h x 7.00w x 0.69d Product Weight: 1.15 lbs. Language: English ISBN: 9781098146825 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 Ships Fast From The USA! Authorized Dealer
Price: 84.99 USD
Location: Milwaukee, Wisconsin
End Time: 2024-11-28T02:37:19.000Z
Shipping Cost: 9.95 USD
Product Images
Item Specifics
Restocking Fee: No
Return shipping will be paid by: Seller
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Book Title: does not apply
Number of Pages: 325 Pages
Language: English
Publication Name: Low-Code Ai : a Practical Project-Driven Introduction to Machine Learning
Publisher: O'reilly Media, Incorporated
Subject: Machine Theory, Programming / Algorithms, Enterprise Applications / Business Intelligence Tools, Intelligence (Ai) & Semantics, Data Processing
Publication Year: 2023
Item Height: 0.7 in
Item Weight: 19.9 Oz
Type: Textbook
Subject Area: Computers
Item Length: 9.2 in
Author: Michael Abel, Gwendolyn Stripling
Item Width: 7.2 in
Format: Trade Paperback
