Meta Learning for Natural Language - Meta Learning for NLP Tasks: Part 3
Part 3 of our tutorial series on Meta Learning for NLP tasks.
2 days ago
Adrien Payong
NLP
public
Meta Learning for Natural Language Processing - Task Construction in meta learning: Part 2
In part 2 of this tutorial series on meta learning for NLP, we discuss different useful techniques for task construction.
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Deep learning techniques for text classification
in this article, we overview several notable techniques for facilitating text classification with deep learning.
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Transformers for Natural Language Reasoning and Automated Symbolic Reasoning Tasks
In this article, we introduce the Transformers package, and detail how it facilitates notable NLP models like RoBERTa, SATformer, GPT-f, and more.
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A Deep Dive into Paperspace's Infrastructure
In this article, we overview the infrastructure that allows Paperspace to serve its powerful GPU, CPU, and IPU machines.
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Introduction to Uncertainty in Machine Learning Models: Aleatoric Uncertainty with TensorFlow Probability - part 2
In part 2 of this series on aleatoric uncertainty, we implement a solution with TensorFlow Probability.
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Introduction to Uncertainty in Machine Learning Models: Concepts and Methods - part 1
In part 1 of this introductory series on uncertainty in ML models, we introduce several proven concepts and methods for identifying two types of uncertainty and evaluating them with statistical methodologies.
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Understanding Reasoning in Large Language Models: Overview of the paper "Towards Reasoning in Large Language Models: A Survey"
In this article, we break down the paper "Towards Reasoning in Large Language Models: A Survey" in an attempt to explain relevant reasoning concepts used by LLMs.
a month ago
