Udemy – Building Recommender Systems with Machine Learning and AI 2019-5

Description

Building Recommender Systems with Machine Learning and AI is the name of a video tutorial on how to design and run recommender engines. In fact, in this course you will learn how to design and implement such a system with the help of machine learning and artificial intelligence. Recommended engines are programs that are able to show you what you like by analyzing different algorithms. The course in front of you has provided you with training from elementary to advanced levels.

The technology mentioned earlier is used in many world-renowned software today. Also, having a minimum of programming experience, especially the Python language, can help you learn better. It should be noted that at the beginning of this course there is an introduction to the Python language. At the end of this course and by learning the concepts and skills taught, you can produce suggestion engines for yourself.

Items that are taught in this course

Learn how to build a recommended engine from scratch

Understand how to filter content using item attributes

Learn modeling-based methods including, matrix factorization and SVD

Learn how to apply Machine Learning and Artificial intelligence

Real-world challenges and solutions that enhance your skills

Combining many recommendation algorithms together in a hybrid and group approach

Course information

English language

Duration: 9 hours and 15 minutes

Number of courses: 110

Level of training: basic to advanced

Instructor: TSundog Education by Frank Kane, Frank Kane

File format: mp4

Course topics Building Recommender Systems with Machine Learning and AI

Course content 110 lectures 09:15:46

Getting Started 7 lectures 33:33

Introduction to Python [Optional] 4 lectures 16:59

Evaluating Recommender Systems 9 lectures 39:51

A Recommender Engine Framework 4 lectures 18:23

Content-Based Filtering 5 lectures 27:17

Neighborhood-Based Collaborative Filtering 13 lectures 53:00

Matrix Factorization Methods 6 lectures 27:14

Introduction to Deep Learning [Optional] 20 lectures 02:27:07

Deep Learning for Recommender Systems 14 lectures 01:17:20

Scaling it Up 9 lectures 50:23

Real-World Challenges of Recommender Systems 11 lectures 35:32

Case Studies 4 lectures 18:40

Hybrid Approaches 2 lectures 07:11

Wrapping Up 2 lectures 03:44

Prerequisite for Building Recommender Systems with Machine Learning and AI

Building Recommender Systems with Machine Learning and AI Requirements

A Windows, Mac, or Linux PC with at least 3GB of free disk space.

Some experience with a programming or scripting language (preferably Python)

Some computer science background, and an ability to understand new algorithms.

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p