TTAML0002 Building Recommendation Systems With Python Training

Recommendation Systems with Python provide good recommendations regarding groceries, friends, and movies, enticing customers to use their platform and define the user experience.

📘 Python 👥 1422 Enrolled ⏱️ 3 Days 💼 Intermediate Level ⭐ 4.9 | 113 Reviews

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Course Overview

In almost every internet business today, professionals will find recommendation systems.

Recommendation Systems with Python provide good recommendations regarding groceries, friends, and movies, enticing customers to use their platform and define the user experience.

This course will make professionals learn about various recommenders used in the industry and from scratch using Python to build them.

Here, professionals will build a content-based engine, an IMDB Top 250 clone, which works on movie metadata.

Professionals will also learn collaborative filtering techniques in this course, helping them grow their careers.

By learning this program, professionals will also learn the extensive functionality of the Python module.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

What you will learn

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

Who Should Attend This Course?

Developers, Analysts, and other professionals interested in learning the tools and techniques needed to build recommendation systems.

Prerequisites

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 us

📞 Talk to a Learning Advisor

📘 TTAML0002 Building Recommendation Systems With Python Outline

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

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

Technical requirements
The simple recommender
The knowledge-based recommender

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

Problem statement
Similarity measures
Clustering
Dimensionality reduction
Supervised learning
Evaluation metrics

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

Technical requirements
Introduction

Still have questions?

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What You Get with Microtek Learning

Instructor-Led Excellence

✓ Certified Instructor-led Training
✓ Top Industry Trainers
✓ Official Student Handbooks

Measurable Learning Outcomes

✓ Pre- & Post-Training Assessments
✓ Practice Tests
✓ Exam-Oriented Curriculum

Real-World Skill Building

✓ Hands-on Activities & Scenarios
✓ Interactive Online Courses
✓ Peer Collaboration (Not in self-paced)

Full Support & Perks

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