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Featured articles
- Attention Mechanisms — The key innovation behind modern Transformer architectures and large language models.
- Neural Networks — From biological inspiration to universal function approximation.
- Gradient Descent — The fundamental optimisation algorithm powering machine learning.
- Stochastic Gradient Descent — The iterative optimisation algorithm behind modern ML training.
- Convolutional Neural Networks — Architectures that revolutionised computer vision.
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| Machine Learning Core concepts, algorithms, and techniques for learning from data. |
Deep Learning Neural network architectures, training techniques, and modern methods. |
| Natural Language Processing Text understanding, language models, and NLP methods. |
Optimisation Algorithms and methods for training machine learning models. |
| Statistics Statistical foundations, probability, and inference methods. |
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- Research Papers — Articles about notable publications in ML and AI
- Summaries — Concise overviews of articles and papers
Notable papers
- Attention Is All You Need (2017) — The Transformer architecture
- BERT Pre-training of Deep Bidirectional Transformers (2019) — Bidirectional pre-training for NLP
- Language Models are Few-Shot Learners (2020) — GPT-3 and in-context learning
- Deep Residual Learning for Image Recognition (2016) — ResNet and skip connections
- Generative Adversarial Nets (2014) — The GAN framework
About Marovi
Marovi aims to make technical knowledge accessible across languages. Our content is enriched through AI-assisted translation and quality pipelines, ensuring accurate and readable articles in multiple languages.
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