Recommender Systems with Machine Learning - Generations of Recommender Systems

The video tutorial discusses the evolution of recommendation systems across three generations. The first generation includes knowledge-based, content-based, and collaborative filtering systems, along with hybrid systems. The second generation introduces matrix factorization, web usage mining, and personality-based approaches. The third generation focuses on advanced techniques like deep learning, product-based systems, and Boltzmann machines. The tutorial also highlights the significance of recommendation systems in artificial intelligence and explores how machine learning and deep learning enhance these systems.

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