Adrien Payong
Deep learning techniques for text classification
in this article, we overview several notable techniques for facilitating text classification with deep learning.
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.
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.
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.
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.
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.
Implement Imagination-Open-Ended Text Generation with INLG
In this tutorial we show how to implement iNLG with Python code in a Gradient Notebook.
Meta Learning for Natural Language Processing: Part 1
In part 1 of this series on meta learning for Natural Language Processing, we introduce optimization and loss functions in machine learning used to approach meta learning with enhanced learning algorithms.