Deep Learning Application for Retail
Offered By: Pluralsight
Course Description
Overview
This course will teach you how deep learning is being used to impact the retail market and shape the future of retail.
AI and machine learning can help tackle complex problems and shape the future of retail. In this course, Deep Learning Application for Retail, you'll learn how deep learning is being used in the real world to drive better business outcomes for retailers. First, you'll explore several practical use cases for deep learning such as customer segmentation, inventory management, and pricing optimization. Next, you'll examine a case study on recommendation engines and discover how personalized product recommendations can be used to promote upsell and cross sell opportunities. Finally, you'll learn how to use machine learning to reduce customer churn and improve your company's bottom line. When you're finished with this course, you will have a better understanding of how deep learning is integrated into our daily lives and how it can be used to make retail businesses more successful.
AI and machine learning can help tackle complex problems and shape the future of retail. In this course, Deep Learning Application for Retail, you'll learn how deep learning is being used in the real world to drive better business outcomes for retailers. First, you'll explore several practical use cases for deep learning such as customer segmentation, inventory management, and pricing optimization. Next, you'll examine a case study on recommendation engines and discover how personalized product recommendations can be used to promote upsell and cross sell opportunities. Finally, you'll learn how to use machine learning to reduce customer churn and improve your company's bottom line. When you're finished with this course, you will have a better understanding of how deep learning is integrated into our daily lives and how it can be used to make retail businesses more successful.
Syllabus
- Course Overview 1min
- Deep Learning in Retail Applications 23mins
- Case Study: Recommendation Systems 13mins
- Case Study: Churn Prediction 16mins
- Summary 4mins
Taught by
Trent McMillan
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