AI & Machine Learning Reference

Machine Learning Fundamentals

Explore the core concepts of machine learning, including supervised, unsupervised, and reinforcement learning.

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Deep Learning Architectures

Dive into common deep learning models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers.

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Natural Language Processing (NLP)

Understand techniques and tools for processing and understanding human language, from sentiment analysis to text generation.

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Computer Vision

Learn about algorithms and applications for enabling computers to "see" and interpret images and videos.

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Reinforcement Learning

Discover how agents learn to make decisions by taking actions in an environment to maximize rewards.

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MLOps Best Practices

Get insights into operationalizing machine learning models, from deployment to monitoring and maintenance.

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AI Ethics & Governance

Understand the ethical considerations and responsible development practices in AI.

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Tools & Frameworks

Overview of popular libraries and platforms like TensorFlow, PyTorch, scikit-learn, and Azure ML.

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