Building Recommendation Systems with Python

Explore Step-by-Step Skills to Develop and Deploy Industry Standard Intelligent Recommendation Systems

TTAML0002

Intermediate

3 Days

Course Overview

Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.

This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.

Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.

Course Objectives

This skills-focused course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern "on-the-job" modern applied datascience, AI and machine learning experience into every classroom and hands-on project.

Working in a hands-on lab environment led by our expert instructor, attendees will

  • Understand the different kinds of recommender systems
  • Master data-wrangling techniques using the pandas library
  • Building an IMDB Top 250 Clone
  • Build a content-based engine to recommend movies based on real movie metadata
  • Employ data-mining techniques used in building recommenders
  • Build industry-standard collaborative filters using powerful algorithms
  • Building Hybrid Recommenders that incorporate content based and collaborative filtering

Need different skills or topics?  If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate.  We offer additional AI, machine learning, data science, programming, Python/R and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.

Course Prerequisites

This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web.

Attending students should have the following incoming skills:

  • Basic to Intermediate IT Skills.
  • Basic Python syntax skills are recommended. Attendees without a programming background like Python may view labs as follow along exercises or team with others to complete them.
  • Good foundational mathematics or logic skills
  • Basic Linux skills, including familiarity with command-line options such as ls, cd, cp, and su

Please see the Related Courses tab for specific Pre-Requisite courses, Related Courses that offer similar skills or topics, and next-step Learning Path recommendations.

Course Agenda

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most.

Getting Started with Recommender Systems

  • Technical requirements
  • What is a recommender system?
  • Types of recommender systems

Manipulating Data with the Pandas Library

  • Technical requirements
  • Setting up the environment
  • The Pandas library
  • The Pandas DataFrame
  • The Pandas Series

Building an IMDB Top 250 Clone with Pandas

  • Technical requirements
  • The simple recommender
  • The knowledge-based recommender

Building Content-Based Recommenders

  • Technical requirements
  • Exporting the clean DataFrame
  • Document vectors
  • The cosine similarity score
  • Plot description-based recommender
  • Metadata-based recommender
  • Suggestions for improvements

Getting Started with Data Mining Techniques

  • Problem statement
  • Similarity measures
  • Clustering
  • Dimensionality reduction
  • Supervised learning
  • Evaluation metrics

Building Collaborative Filters

  • Technical requirements
  • The framework
  • User-based collaborative filtering
  • Item-based collaborative filtering
  • Model-based approaches

Hybrid Recommenders

  • Technical requirements
  • Introduction
  • Case study and final project – Building a hybrid model

Course Materials

Each student will receive a Student Guide with course notes, code samples, software tutorials, step-by-step written lab instructions, diagrams and related reference materials and links (as applicable). Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work.

Lab Setup Made Simple.   All course labs and solutions, data sets, Tableau course software (limited version, for course use only), detailed courseware, lab guides and resources (as applicable) are provided for attendees in our easy access, no installation required, remote lab environment for the duration of the course. Our tech team will help set up, test and verify lab access for each attendee prior to the course start date, ensuring a smooth start to class and successful hands-on course experience for all participants. 

Raise the bar for advancing technology skills

Attend a Class!

Live scheduled classes are listed below or browse our full course catalog anytime

Special Offers

We regulary offer discounts for individuals, groups and corporate teams. Contact us

Custom Team Training

Check out custom training solutions planned around your unique needs and skills.

EveryCourse Extras

Exclusive materials, ongoing support and a free live course refresh with every class.

Attend a Course

Please see the current upcoming available open enrollment course dates posted below. Please feel free to Register Online below, or call 844-475-4559 toll free to connect with our Registrar for assistance. If you need additional date options, please contact us for scheduling.

Course Title Days Date Time Price
Building Recommendation Systems with Python 3 Days Apr 7 to Apr 9 10:00 AM to 06:00 PM EST $2,495.00 Register
Building Recommendation Systems with Python 3 Days Jun 9 to Jun 11 10:00 AM to 06:00 PM EST $2,495.00 Register
Building Recommendation Systems with Python 3 Days Aug 11 to Aug 13 10:00 AM to 06:00 PM EST $2,495.00 Register
Building Recommendation Systems with Python 3 Days Oct 13 to Oct 15 10:00 AM to 06:00 PM EST $2,495.00 Register
Building Recommendation Systems with Python 3 Days Dec 8 to Dec 10 10:00 AM to 06:00 PM EST $2,495.00 Register

New Site, BIG Savings!
We're celebrating the launch of our lonnngggg awaited new site with with *50% off all 2021 Public Classes* booked by March 31!  Check out our Current Offers for Individuals, Teams and Organizations to Learn for Less!

See our latest Offers and Promotions

Learn. Explore. Advance!

Extend your training investment! Recorded sessions, free re-sits and after course support included with Every Course
Trivera MiniCamps
Gain the skills you need with less time in the classroom with our short course, live-online hands-on events
Trivera QuickSkills: Free Courses and Webinars
Training on us! Keep your skills current with free live events, courses & webinars
Trivera AfterCourse: Coaching and Support
Expert level after-training support to help organizations put new training skills into practice on the job

The voices of our customers speak volumes

Special Offers
Limited Offer for most courses.

SAVE 50%

Learn More