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Deep Learning Application for Retail
Trent McMillan
Trent McMillan
This course will teach you how deep learning is being used to impact the retail market and shape the future of retail.
Read more
This course will teach you how deep learning is being used to impact the retail market and shape the future of retail.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/1xt8id/deep
What's inside
Syllabus
Course Overview
Deep Learning in Retail Applications
Case Study: Recommendation Systems
Case Study: Churn Prediction
Read more
Syllabus
Course Overview
Deep Learning in Retail Applications
Case Study: Recommendation Systems
Case Study: Churn Prediction
Read more
Summary
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops practical applications of Deep Learning for enhancing customer experience in retail settings
Teaches how to leverage AI and machine learning to address complex challenges and shape the future of retail
Examines real-world use cases of Deep Learning in retail, showcasing its impact on business outcomes
Delves into case studies on recommendation engines and churn prediction, providing hands-on experience with key applications
Suitable for retail professionals seeking to leverage Deep Learning to improve customer segmentation, inventory management, and pricing optimization
Provides practical insights into reducing customer churn using machine learning techniques
Taught by experienced instructors, Trent McMillan, known for their expertise in Deep Learning applications
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Deep Learning Application for Retail.
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Career center
Learners who complete Deep Learning Application for Retail will develop knowledge and skills
that may be useful to these careers:
Retail Analyst
Retail Analyst
A Retail Analyst analyzes data to make informed decisions about retail operations. This course in Deep Learning Application for Retail is a perfect fit for someone who wants to become a Retail Analyst. Retail Analysts need to have a deep understanding of the retail industry and how to use data to improve retail operations. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning systems to solve business problems. This course in Deep Learning Application for Retail will help you to become a Machine Learning Engineer. It provides you with a strong foundation in the fundamentals of machine learning. It also teaches you how to use deep learning techniques to solve real-world problems in the retail industry. By the end of this course, you will have the skills and knowledge you need to build and deploy machine learning systems that can improve business outcomes for retailers.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make informed investment decisions. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Financial Analyst. Financial Analysts need to have a strong understanding of financial markets and how to use data to make investment decisions. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Data Scientist
Data Scientist
A Data Scientist analyzes data to extract meaningful insights and trends that can be used by businesses to improve their decision-making. This course in Deep Learning Application for Retail is a valuable stepping stone for one who wants to become a Data Scientist. Data Scientists need to have a strong foundation in mathematics, statistics, and machine learning techniques. This course helps build a foundation in these areas and gives students the opportunity to practice using machine learning techniques on real-world data. It also provides students with an understanding of how deep learning is used to drive better business outcomes for retailers.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Software Engineer. Software Engineers need to have a strong understanding of software engineering principles and how to use data to solve business problems. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Data Engineer
Data Engineer
A Data Engineer builds and maintains data pipelines. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Data Engineer. Data Engineers need to have a strong understanding of data engineering principles and how to use data to solve business problems. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Sales Manager
Sales Manager
A Sales Manager is responsible for managing a sales team and achieving sales goals. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Sales Manager. Sales Managers need to have a deep understanding of the sales process and how to use data to drive sales decisions. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Marketing Manager
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Marketing Manager. Marketing Managers need to have a deep understanding of the marketing process and how to use data to drive marketing decisions. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Customer Success Manager
Customer Success Manager
A Customer Success Manager is responsible for ensuring that customers are satisfied with their products or services. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become a Customer Success Manager. Customer Success Managers need to have a deep understanding of the customer experience and how to use data to improve it. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Business Analyst
Business Analyst
A Business Analyst uses data and analysis to identify and solve business problems. This course in Deep Learning Application for Retail is a valuable stepping stone for one who wants to become a Business Analyst. Business Analysts need to have a strong understanding of business processes and how to use data to improve them. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Operations Manager
Operations Manager
An Operations Manager is responsible for overseeing the day-to-day operations of a business. This course in Deep Learning Application for Retail is a valuable stepping stone for someone who wants to become an Operations Manager. Operations Managers need to have a deep understanding of the business and how to use data to improve operations. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Consultant
Consultant
A Consultant provides advice and guidance to businesses on a variety of topics. This course in Deep Learning Application for Retail may be useful for someone who wants to become a Consultant. Consultants need to have a deep understanding of the business world and how to use data to solve business problems. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course in Deep Learning Application for Retail may be useful for someone who wants to become a Product Manager. Product Managers need to have a strong understanding of the product development process and how to use data to drive product decisions. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Entrepreneur
Entrepreneur
An Entrepreneur starts and runs their own business. This course in Deep Learning Application for Retail may be useful for someone who wants to become an Entrepreneur. Entrepreneurs need to have a deep understanding of the business world and how to use data to make informed decisions. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
Data Analyst
Data Analyst
A Data Analyst uses data to make informed decisions. This course in Deep Learning Application for Retail may be useful to someone who wants to become a Data Analyst. Data Analysts need to have a strong foundation in mathematics, statistics, and data analysis techniques. This course will help you to develop these skills. It will also introduce you to deep learning techniques that can be used to analyze data more effectively.
For more career information including salaries, visit:
OpenCourser.com/course/1xt8id/deep
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Deep Learning Application for Retail.
Serves as an excellent reference for understanding the fundamentals of deep learning and its implementation using Python. It provides a strong foundation for applying deep learning techniques in retail.
Offers a hands-on approach to machine learning using popular libraries like Scikit-Learn, Keras, and TensorFlow. It provides a practical guide to building and evaluating machine learning models.
Highlights the importance of customer experience in retail and provides strategies for building lasting customer relationships. It complements the course's focus on deep learning by emphasizing the human aspect of retail.
Provides a rigorous treatment of statistical learning algorithms, including supervised and unsupervised methods. It serves as an excellent reference for understanding the theoretical underpinnings of deep learning techniques.
Focuses on deep learning applications in computer vision, which is relevant to certain aspects of retail, such as image recognition and object detection.
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Provides a comprehensive overview of natural language processing (NLP) using deep learning techniques. It is valuable for understanding how NLP can be applied in retail, such as for chatbots or product descriptions.
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Offers a practical guide to predictive modeling, covering topics like data preparation, model selection, and evaluation. It provides a solid foundation for applying deep learning for prediction tasks in retail.
Provides a probabilistic approach to machine learning, offering a deeper understanding of the underlying principles. It is beneficial for learners who want to explore the theoretical foundations of deep learning.
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Offers a comprehensive overview of data mining techniques, including machine learning algorithms. It provides a solid background for learners who want to further explore the fundamentals of machine learning.
Provides a practical introduction to machine learning, covering various algorithms and their applications. It offers a gentle introduction to machine learning concepts.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1xt8id/deep
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Time
60 hours
Level
Introductory
Via
Pluralsight
Instructor
Trent McMillan
Language
English
Good to know
Develops practical applications of Deep Learning for enhancing customer experience in retail settings
Teaches how to leverage AI and machine learning to address complex challenges and shape the future of retail
Examines real-world use cases of Deep Learning in retail, showcasing its impact on business outcomes
Delves into case studies on recommendation engines and churn prediction, providing hands-on experience with key applications
Suitable for retail professionals seeking to leverage Deep Learning to improve customer segmentation, inventory management, and pricing optimization
Provides practical insights into reducing customer churn using machine learning techniques
Taught by experienced instructors, Trent McMillan, known for their expertise in Deep Learning applications
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