Machine Learning Fundamentals: Learning to Make Recommendations

Machine Learning Fundamentals: Learning to Make Recommendations

Website or Online Data - 2017
Rate this:
This project-based course shows programmers of all skill levels how to use machine learning to build programs that can make recommendations. In this course, Adam Geitgey walks you through a hands-on lab building a recommendation system that is able to suggest similar products to customers based on past products they have reviewed or purchased. The system can also identify which products are similar to each other. Recommendation systems are a key part of almost every modern consumer website. The systems help drive customer interaction and sales by helping customers discover products and services they might not ever find themselves. The course uses the free, open source tools Python 3.5, pandas, and numpy. By the end of the course, you'll be equipped to use machine learning yourself to solve recommendation problems. What you learn can then be directly applied to your own projects.
This project-based course shows programmers of all skill levels how to use machine learning to build programs that can make recommendations--like recommending new products to customers based on how they reviewed other products.
Publisher: Carpenteria, CA : lynda.com, 2017
Copyright Date: ©2017
Characteristics: 1 online resource
Additional Contributors: lynda.com (Firm)
Call Number: eResearch

Opinion

From the critics


Community Activity

Comment

Add a Comment

There are no comments for this title yet.

Age

Add Age Suitability

There are no ages for this title yet.

Summary

Add a Summary

There are no summaries for this title yet.

Notices

Add Notices

There are no notices for this title yet.

Quotes

Add a Quote

There are no quotes for this title yet.

Explore Further

Recommendations

Subject Headings

  Loading...

Find it at DCL

  Loading...
[]
[]
To Top