Enroll Course: https://www.udemy.com/course/best-recommender-system/
Are you looking to build powerful recommendation engines that drive user engagement and personalize experiences? Look no further than Frank Kane’s comprehensive Udemy course, “Building Recommendation Systems with Machine Learning & AI” (with Korean subtitles available!). As an ex-Amazon engineer who spent nine years developing Amazon’s personalization and recommendation technologies, Frank brings unparalleled real-world expertise to this hands-on course.
This isn’t just a coding tutorial; it’s a deep dive into the ‘why’ and ‘how’ of recommendation systems. Frank guides you through the evolution of recommendation algorithms, starting from foundational neighborhood-based collaborative filtering and progressing to cutting-edge techniques like matrix factorization and deep learning with neural networks. You’ll gain a practical understanding of the challenges faced when applying these algorithms to large datasets, all explained through Frank’s engaging industry experience.
The course is heavily practical, empowering you to develop your own framework, combine various recommendation algorithms, and evaluate their performance. You’ll even build your own neural networks using TensorFlow and construct a real-world movie rating recommendation system.
Key topics covered include:
* Recommendation engine creation and evaluation
* Content-based filtering using item attributes
* Neighborhood-based collaborative filtering (user-based, item-based, KNN CF)
* Model-based methods like matrix factorization and SVD
* Applying deep learning, AI, and neural networks
* Utilizing modern frameworks like TensorFlow Recommenders (TFRS) and Amazon Personalize
* Session-based recommendations with Recurrent Neural Networks
* Scaling with Apache Spark ML, Amazon DSSTNE, and AWS SageMaker
* Real-world challenges and solutions in recommendation systems
* Case studies from YouTube and Netflix
* Building hybrid and ensemble recommendation systems
* Latest research in the field with “Bleeding edge alerts”
While the course includes an introduction to Python for beginners, prior programming experience is recommended. A brief introduction to deep learning is also provided, but a solid understanding of computer algorithms is beneficial.
Frank Kane is a top instructor with over 810,000 students worldwide, and this course has been updated with TensorFlow Recommenders (TFRS) and Generative Adversarial Networks (GANs) for recommendations. Understanding these technologies is crucial for landing roles at top tech companies.
If you’re serious about mastering recommendation systems and want to learn from a true industry pioneer, this course is an absolute must-have. Frank’s clear explanations and practical approach make complex topics accessible and actionable. Don’t miss this opportunity to elevate your skills in a highly sought-after field!
Enroll Course: https://www.udemy.com/course/best-recommender-system/