Lynda - Machine Learning Fundamentals: Learning to Make Recommendations
Lynda - Machine Learning Fundamentals: Learning to Make Recommendations
Size: 138 MB | Duration: 0h 58m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English
Size: 138 MB | Duration: 0h 58m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Intermediate | Language: English
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.
* Building a machine learning system
* Training a machine learning system
* Refining the accuracy of the machine learning system
* Evaluating the recommendations received
* Training a machine learning system
* Refining the accuracy of the machine learning system
* Evaluating the recommendations received
Lynda - Machine Learning Fundamentals: Learning to Make Recommendations
No mirrors below please.