Description: Supervised Machine Learning by Tanya Kolosova, Samuel Berestizhevsky Estimated delivery 3-12 business days Format Paperback Condition Brand New Description AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises of bootstrapping to create multiple training and testing data sets, design and analysis of statistical experiments and optimal hyper-parameters for ML methods. Publisher Description AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. The AI framework comprises of bootstrapping to create multiple training and testing data sets with various characteristics, design and analysis of statistical experiments to identify optimal feature subsets and optimal hyper-parameters for ML methods, data contamination to test for the robustness of the classifiers. Key Features: Using ML methods by itself doesnt ensure building classifiers that generalize well for new data Identifying optimal feature subsets and hyper-parameters of ML methods can be resolved using design and analysis of statistical experiments Using a bootstrapping approach to massive sampling of training and tests datasets with various data characteristics (e.g.: contaminated training sets) allows dealing with bias Developing of SAS-based table-driven environment allows managing all meta-data related to the proposed AI framework and creating interoperability with R libraries to accomplish variety of statistical and machine-learning tasks Computer programs in R and SAS that create AI framework are available on GitHub Author Biography Tanya Kolosova is a statistician, software engineer, an educator, and a co-author of two books on statistical analysis and metadata-based applications development using SAS. Tanya is an actionable analytics expert, she has extensive knowledge of software development methods and technologies, artificial intelligence methods and algorithms, and statistically designed experiments. Samuel Berestizhevsky is a statistician, researcher and software engineer. Together with Tanya, Samuel co-authored two books on statistical analysis and metadata-based applications development using SAS. Samuel is an innovator and an expert in the area of automated actionable analytics and artificial intelligence solutions. His extensive knowledge of software development methods, technologies and algorithms allows him to develop solutions on the cutting edge of science. Details ISBN 0367538822 ISBN-13 9780367538828 Title Supervised Machine Learning Author Tanya Kolosova, Samuel Berestizhevsky Format Paperback Year 2022 Pages 182 Publisher Taylor & Francis Ltd GE_Item_ID:135418524; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 75.35 USD
Location: Fairfield, Ohio
End Time: 2024-11-02T03:35:15.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9780367538828
Book Title: Supervised Machine Learning
Number of Pages: 182 Pages
Language: English
Publication Name: Supervised Machine Learning : Optimization Framework and Applications with Sas and R
Publisher: CRC Press LLC
Subject: Machine Theory, Mathematical & Statistical Software, General, Statistics
Publication Year: 2022
Type: Textbook
Item Weight: 16 Oz
Author: Tanya Kolosova, Samuel Berestizhevsky
Item Length: 9.2 in
Subject Area: Computers, Science, Business & Economics
Item Width: 6.1 in
Format: Trade Paperback