Booking options
Price on Enquiry
Price on Enquiry
Delivered Online
3 days
All levels
Duration
3 Days
18 CPD hours
This course is intended for
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.
Overview
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
Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix 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.This skills-focused ccombines 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.
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
Additional course details:
Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.
This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.
Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.
While we feel this is the best course for the Applied AI: Building Recommendation Systems with Python (TTAI2360) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.
Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Nexus Human, established over 20 years ago, stands as a pillar of excellence in the realm of IT and Business Skills Training and education in Ireland and the UK....