Hrishikesh Kamath

Discusses methods for curating fine-tuning datasets for Large Language Models, focusing on a data-centric approach.

Explores the differences and implications of model-centric versus data-centric approaches in machine learning.

A guide on how to analyze private datasets effectively using the Pandas library.

An introductory overview of weakly supervised learning techniques.

Discusses Meta-Learning using the Model-Agnostic Meta-Learning (MAML) algorithm.

Covers machine learning approaches for predicting classes that were not encountered during the training phase.

Insights into practical applications of deep learning and understanding the algorithmic perspective.

The second part of a series on differential privacy, focusing on various mechanisms for achieving privacy.

The first part of a series introducing the concept of differential privacy.