Practical Recommender Systems For Business Applications in R

ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BUILDING PRACTICAL RECOMMENDER SYSTEMS WITH RAre 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 PreferencesBy 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 systemsMY 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 dataMy 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).