Building Recommender Systems with Machine Learning and AI
Master Recommender Systems with 12 hours of hands-on Machine Learning and Deep Learning training led by expert Frank Kane—use coupon SUNDOG1M to enroll now!
Table of Contents
Overview of Building Recommender Systems with Machine Learning and AI Course on Udemy
Discover how to create powerful recommender systems with the Building Recommender Systems with Machine Learning and AI course on Udemy. Led by Frank Kane, a former Amazon engineer with over nine years of experience in recommendation technologies, this 12-hour on-demand video course includes 4 articles and 44 downloadable resources. You’ll learn to build machine learning and deep learning systems using Python, covering techniques like collaborative filtering and neural networks to recommend products or content. With lifetime access, mobile and TV compatibility, and a certificate of completion, this course is ideal for developers and data scientists aiming to enhance user experiences. Enroll today with udemy coupon codes SUNDOG1M (valid until July 31, 2025—check the offer box below for the discount link!)
What to Expect from the Building Recommender Systems with Machine Learning and AI Course
This 12-hour course offers a hands-on, project-based learning experience, guiding you through building recommendation engines with Python and frameworks like TensorFlow. Frank Kane’s teaching style combines real-world insights with practical examples, such as movie and product recommendations, making it suitable for intermediate developers and data professionals. The course covers over 20 hands-on projects, from basic collaborative filtering to advanced neural collaborative filtering, and is accessible on Udemy’s platform across mobile, TV, and desktop for flexible learning.
What You Will Learn in Building Recommender Systems with Machine Learning and AI
- Implement user-based collaborative filtering to recommend items based on user preferences.
- Build neural networks using TensorFlow for advanced recommendation systems.
- Apply matrix factorization techniques like SVD and SVD++ for accurate predictions.
- Scale recommendations with Apache Spark for large datasets on AWS EC2 clusters.
- Use TensorFlow Recommenders (TFRS) for state-of-the-art recommendation algorithms.
- Address real-world challenges like the cold start problem with content-based filtering.
Why Choose This Building Recommender Systems with Machine Learning and AI Course on Udemy
This course is a top choice due to Frank Kane’s extensive experience at Amazon, where he pioneered personalized recommendation systems. With 12 hours of video, 4 articles, and 44 downloadable resources, it offers comprehensive, practical training for building recommendation engines. The hands-on projects, such as creating movie recommendation systems, ensure skills are industry-relevant. Updated for 2025, it includes modern techniques like Neural Collaborative Filtering. Use udemy promo codes SUNDOG1M to get at a discount (see offer box)
Recommended Courses with Recommender Systems and AI Focus
Looking to expand your skills? Check out these related courses:
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[2025] Tensorflow 2: Deep Learning & Artificial Intelligence
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Our Review of Building Recommender Systems with Machine Learning and AI Course
From a website admin perspective, this course is a standout for its depth and practicality in teaching recommender systems. Frank Kane’s industry expertise shines through, with clear explanations and hands-on projects like building movie recommendation engines. The course’s focus on both foundational and advanced techniques, such as TensorFlow Recommenders, makes it highly valuable, though it assumes intermediate Python skills, which may challenge beginners. The extensive resources and real-world focus ensure actionable learning.
- Pros:
- Over 20 hands-on projects enhance practical AI skills.
- Covers modern tools like Apache Spark and Neural Collaborative Filtering.
- Lifetime access and mobile compatibility offer flexibility.
- Cons:
- Requires intermediate Python and programming knowledge, limiting accessibility for novices.
- Some advanced topics could benefit from slower pacing for clarity.
With udemy courses coupon SUNDOG1M, it’s a steal!
Rating the Building Recommender Systems with Machine Learning and AI Course
- Content: 9.3/10 – Comprehensive coverage of recommender systems, from collaborative filtering to deep learning.
- Delivery: 8.8/10 – Engaging and clear, though pacing may vary for complex topics.
- Value: 9.5/10 – Affordable with udemy discounts coupon SUNDOG1M.
Enroll now to master recommendation engines with this top-tier course!
Additional Information from Search Insights
This course aligns with trending search keywords like recommender systems, machine learning, deep learning, collaborative filtering, TensorFlow Recommenders, matrix factorization, Apache Spark, Neural Collaborative Filtering, Python, and cold start problem. These terms reflect the high demand for expertise in personalized recommendations, critical for industries like e-commerce, streaming, and social media. By offering hands-on training in Python and modern AI techniques, this course equips learners to meet the needs of a competitive, data-driven market.
