Intermediate Unsupervised Learning

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The Essential Main Ideas of Neural Networks

Learn Machine Learning Like a GENIUS and Not Waste Time

All Machine Learning algorithms explained in 17 min

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Transformers Explained - How transformers work

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Transformer Neural Networks - EXPLAINED! (Attention is all you need)

This course teaches you how to use R to apply clustering, dimensionality reduction, and anomaly detection techniques to explore and analyze unlabeled datasets, including algorithms like k-means, hierarchical clustering, and DBSCAN.

Learn DeepLearning.AI Unsupervised Learning, Recommenders, Reinforcement Learning

Top-down approach to deep learning using the fast.ai library. Build state-of-the-art models without needing a PhD.

Explore how to make powerful, accurate predictions with ensemble learners, one of the most common classes of machine learning algorithms.

This course shows you how to apply supervised learning techniques to real-world problems, focusing on both classification and regression tasks. You'll start with basic models and advance to more complex algorithms like decision trees and XG Boost.

Learn to train state-of-the-art models in computer vision, NLP, tabular data, and collaborative filtering. No PhD required!