Recommender System With Machine Learning and Statistics
https://CourseMega.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 13 lectures (54m) | Size: 445.5 MB
Step-By-Step Guide to Build Collaborative Filtering and Association Rule Based Recommender Using Fastai and Python
What you'll learn:
Understand the hypotheses behind the main solutions of recommender systems
Build and train collaborative filtering models with fastai
Fetch and visualize latent features
Compare and interpret weights and biases
Compute support, confidence, and lift
Encode an item-order matrix
Apply association rule and Apriori algorithm
Evaluate results with selected criteria
Exercise the trained model on large test datasets
Requirements
Understand basic concepts in machine learning, statistics, and python
Description
Recommender system is a promising approach to boost sales to the next level by suggesting the right products to the right customers.
This course starts by showing you the main solutions of recommender systems in the industry and the hypotheses behind the main solutions. You’ll then learn how to build collaborative filtering models with fastai, and exercise the trained model on test datasets.