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Predicting Reaction Yields with Deep Learning
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Scaling Language Models: Efficiency and Deployment
Covers the scaling of language models, focusing on training efficiency and deployment considerations.
Introduction to Financial Markets and Time Series
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Natural Language Processing: Understanding Transformers and Tokenization
Provides an overview of Natural Language Processing, focusing on transformers, tokenization, and self-attention mechanisms for effective language analysis and synthesis.
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Graph Machine Learning
Delves into graph-enhanced machine learning, focusing on fraud detection, malware detection, and recommendation systems.
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Active Learning for Molecular Design
Covers machine learning approaches for material design, practical examples, and software tools for research.
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Covers the role of Transformers in unifying various machine learning fields.
Transformers in Vision: Applications and Architectures
Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.
Language Models: Fixed-context and Recurrent Neural Networks
Discusses language models, focusing on fixed-context neural models and recurrent neural networks.