Practical Recommender Systems For Business Applications in R

Implementing Data Science Driven Recommender Systems For Business Applications With R

4.90 (16 reviews)
Udemy
platform
English
language
Databases
category
instructor
1,148
students
3.5 hours
content
Apr 2022
last update
$64.99
regular price

What you will learn

Learn what recommender systems are and their importance for business intelligence

Learn the main aspects of implementing data science technique within the R Programming Language

Implement practical recommender systems using R Programming Language

Learn about the theoretical and practical aspects of recommender systems

Description

ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BUILDING PRACTICAL RECOMMENDER SYSTEMS WITH R


  • Are you interested in learning how the Big Tech giants like Amazon and Netflix recommend products and services to you?

  • Do you want to learn how data science is hacking the multibillion e-commerce space through recommender systems?

  • Do you want to implement your own recommender systems using real-life data?

  • Do you want to develop cutting edge analytics and visualisations to support business decisions?

  • Are you interested in deploying machine learning and natural language processing for making recommendations based on prior choices and/or user profiles?

You Can Gain An Edge Over Other Data Scientists If You Can Apply R Data Analysis Skills For Making Data-Driven Recommendations Based On User Preferences


  • By enhancing the value of your company or business through the extraction of actionable insights from commonly used structured and unstructured data commonly found in the retail and e-commerce space

  • Stand out from a pool of other data analysts by gaining proficiency in the most important pillars of developing practical recommender systems


MY COURSE IS A HANDS-ON TRAINING WITH REAL RECOMMENDATION RELATED PROBLEMS- You will learn to use important R data science techniques to derive information and insights from both structured data (such as those obtained in typical retail and/or business context) and unstructured text data

My course provides a foundation to carry out PRACTICAL, real-life recommender systems tasks using Python. By taking this course, you are taking an important step forward in your data science journey to become an expert in deploying the R Programming data science techniques for answering practical retail and e-commerce questions (e.g. what kind of products to recommend based on their previous purchases or their user profile).

Why Should You Take My Course?

I have an MPhil (Geography and Environment) from the University of Oxford, UK. I also completed a data science intense PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real-life data from different sources and producing publications for international peer-reviewed journals.

This course will help you gain fluency in deploying data science-based recommended systems in R to inform business decisions. Specifically, you will


  • Learn the main aspects of implementing data science techniques in the R Programming Language

  • Learn what recommender systems are and why they are so vital to the retail space

  • Learn to implement the common data science principles needed for building recommender systems

  • Use visualisations to underpin your glean insights from structured and unstructured data

  • Implement different recommender systems in the R Programming Language

  • Use common natural language processing (NLP) techniques to recommend products and services based on descriptions and/or titles


    You will work on practical mini case studies relating to (a) Online retail product descriptions (b) Movie ratings (c) Book ratings and descriptions to name a few

In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!

ENROLL NOW :)

Content

Welcome to the Course

What Is the Course About?
Data and Code
Install R and RStudio
Different Data Types
Why Recommender Systems?

Basic R Programming

Read CSV and Excel Data
Read in Data from Online HTML Tables-Part 1
Read in Data from Online HTML Tables-Part 2
Data Cleaning
More Data Cleaning
Pre-processing Tasks and the Pipe Operator
DPLYR-1
DPLYR-2
Some Joining
The Tall and Short Of It
Visualize Ratings

Basic Statistical Concepts Underpinning Recommender Systems

Principal Components Analysis (PCA)-Theory
Implement PCA in R
Single Vector Decomposition (SVD)- Theory
Implement SVD in R
Unsupervised Learning-Theory
k-Means Clustering-Theory
K-Means Implementation
Supervised Learning-Theory
Cosine Similarity

What Are Recommender Systems?

Different Types of Recommender Systems
The Recommenderlab Package
Prepare Your Data For Use in Recommenderlab
A Simple Cosine Similarity Based Recommender Engine
Explore Other Recommenderlab Models
Collaborative Filtering With Cosine Similarity
Clustering For Identifying Similar Books
Identify Top Reader Preferences
Item Based Recommendations

Miscellaneous Section

Using R Within Colab
What Are Wordclouds?

Screenshots

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Reviews

Shaon
August 12, 2023
An excellent course here is mentioned to all the social media that our person will provide life assistance.
kamal
August 12, 2023
You are amazing. Your teaching is very clear and easy to understand. Thank you so much. Hope you will add more content to the course in near future.
Sakira
August 12, 2023
It is pretty good course .Everything is Very clear explanations and well designed and organized course.
Joynal
August 12, 2023
Everything well explained and clear. The course is complete and really easy to follow. I can feel all the effort and passion you put inside to create this course.
al
August 12, 2023
This is a very important course. I benefited a lot from the course. I hope all the topics of this course will be useful in the future.
Kamlesh
April 17, 2023
An amazing course. Beyond my expectations. It will enhance the quality of my work several times. the instructor's knowledge of the subject is impressive.
Anonymized
February 25, 2023
It is an amazing course . It contains vital and useful information which has immense practical value.
Rajesh
June 27, 2022
The course contains valuable information on the subject and has vast potential for practical applications.

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8/12/2023100% OFF
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4605750
udemy ID
3/21/2022
course created date
4/30/2022
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