unsupervised learning

Apriori Algorithm in Data Mining: Working, Applications & Association Rule Learning

What is Apriori Algorithm? Large transactional databases can be mined for frequent itemsets and association rules using the traditional Apriori approach. Finding patterns of items that commonly co-occur in transactions…

Generative Adversarial Networks (GANs): Architecture, Working & Applications in AI

What is Generative Adversarial Networks (GANs)? Ian Goodfellow invented Generative Adversarial Networks (GANs) in 2014 as a kind of machine learning technique for generative modeling. Their main purpose is to…

Autoencoders (AE) in Deep Learning: Architecture, Types & Real-World Applications

What is Autoencoders (AE) Algorithm? An Artificial Neural Network type called an Autoencoder (AE) is used for unsupervised learning. Its objective is to learn effective data representations, usually for feature…

FP-Growth Algorithm in Data Mining: Fast Frequent Pattern Mining Explained

What is FP-Growth (Frequent Pattern Growth)? An effective and scalable technique for mining frequent itemsets in big transactional databases is the FP-Growth (Frequent Pattern Growth) algorithm. By employing a tree-based…

Deep Belief Networks (DBN): Architecture, Training Process & Applications in Deep Learning

What is Deep Belief Networks (DBN) Algorithm? One kind of deep learning model is called a Deep Belief Network (DBN), which is composed of several layers of unsupervised learning models…

Apriori Algorithm in Data Mining: Working, Applications & Association Rule Learning

Generative Adversarial Networks (GANs): Architecture, Working & Applications in AI

Autoencoders (AE) in Deep Learning: Architecture, Types & Real-World Applications

FP-Growth Algorithm in Data Mining: Fast Frequent Pattern Mining Explained

Deep Belief Networks (DBN): Architecture, Training Process & Applications in Deep Learning

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