Data is the new fuel of the modern world and artificial intelligence is the accelerator. Almost every aspect of our modern life is influenced by data-driven systems. A recommender system is one such system that leverages historical usage data to provide personalized recommendations to customers improving overall customer experience and increasing the sales and revenue for the enterprise. In this course, Literacy Essentials: Core Concepts Recommender Systems, you’ll learn to build recommendation engines with the help of Python. First, you’ll learn what recommendation systems are and explore how to evaluate them. Next, you’ll discover different types of recommendation techniques. Then, you’ll explore collaborative filtering in detail. Finally, you’ll cover how to build state-of-the-art recommendations systems for a global enterprise using Python. When you’re finished with this course, you’ll have the skills and knowledge of Literacy Essentials: Core Concepts Recommender Systems needed to enhance the sales as well as the user experience based on appropriate product suggestions.
Author Name: Biswanath Halder
Author Description:
Biswanath is a Data Scientist who has around nine years of working experience in companies like Oracle, Microsoft, and Adobe. He has extensive knowledge of Machine Learning, Deep Learning, and Reinforcement Learning. He specializes in applying Machine Learning and Deep Learning techniques in complex business applications related to computer vision and natural language processing. He is also a freelance educator and teaches Statistics, Mathematics, and Machine Learning. He holds a Master’s degre… more

Table of Contents

• Course Overview
  1min
• Introduction to Recommendation Systems
  11mins
• Collaborative-filtering Based Recommendation Systems
  19mins
• Build a Product Recommendation System for Globomantics Using Python
  18mins
• Other Approaches to Generate Recommendations
  13mins