Building Intelligent Recommender Systems: Practical Insights for Engineers by Ma

Description: Building Intelligent Recommender Systems by Madeleine Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Recommender systems have become an integral part of our daily lives, playing a significant role in shaping our online experiences. From suggesting movies on streaming platforms to recommending products on e-commerce websites, these systems have revolutionized the way we discover and consume content. In this subchapter, we will delve into the fundamentals of recommender systems, providing practical insights for engineers in the niche fields of data science and machine learning.At its core, a recommender system is an algorithmic approach that predicts and provides users with personalized recommendations based on their preferences, historical behavior, and other relevant data. By understanding user preferences and leveraging the power of machine learning, these systems aim to deliver relevant and personalized content, enhancing user satisfaction and engagement.One of the key challenges in building intelligent recommender systems lies in capturing and representing user preferences accurately. Collaborative filtering, content-based filtering, and hybrid approaches are some of the popular techniques used for generating recommendations. Collaborative filtering analyzes user behavior and preferences to find similarities among users or items, while content-based filtering focuses on the attributes of items to recommend similar ones. Hybrid approaches combine the strengths of both techniques to provide more accurate and diverse recommendations.Engineers working in the data science and machine learning fields must be well-versed in the underlying algorithms and methodologies used in recommender systems. Matrix factorization, deep learning, and reinforcement learning are some of the advanced techniques employed for improving recommendation accuracy and addressing cold-start problems.However, building intelligent recommender systems is not solely about algorithms and models. Engineers must also consider factors such as data quality, scalability, interpretability, and ethics. The book "Building Intelligent Recommender Systems: Practical Insights for Engineers" aims to equip engineers with a comprehensive understanding of these factors, providing practical guidance and real-world examples to design and deploy robust recommender systems. Details ISBN-13 9798869058577 Title Building Intelligent Recommender Systems Author Madeleine Format Paperback Year 2023 Pages 118 Publisher Independent GE_Item_ID:157870485; 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

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