Category: Machine Learning

We can use data to train machines to perform tasks instead of explicitly programming them. This category will cover experiments utilizing neural networks, graph neural networks, and probabilistic approaches to train machines to perform tasks using data

Embeddings

Published November 1, 2022

Recent successes in machine learning owe their power to transfer and representation learning. Transfer learning allows us to fine-tune a model trained on one task to a new task using fewer training examples and improving accuracy. Representation learning is allowing a system to discover the representations required for feature detection…

Transfer in Machine Learning

Published July 8, 2022

Transfer learning is a process through which a machine learning model trained for a different task, is fine-tuned to a new task. Through this process, the knowledge that the earlier model had learned is transferred to the new task, which can take advantage of the learned patterns. In human learning,…