<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://pulkit1704.github.io//</id><title>Blog</title><subtitle>Technical notes from a biological sciences researcher and ML practitioner. Insights on machine learning and deep learning architectures applied to genomics and molecular biology.</subtitle> <updated>2026-05-24T15:04:41+00:00</updated> <author> <name>Pulkit</name> <uri>https://pulkit1704.github.io//</uri> </author><link rel="self" type="application/atom+xml" href="https://pulkit1704.github.io//feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://pulkit1704.github.io//"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2026 Pulkit </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Peering into the Black Box: Various Perspectives to Neural Network training</title><link href="https://pulkit1704.github.io//posts/deep-learning-mechanics/" rel="alternate" type="text/html" title="Peering into the Black Box: Various Perspectives to Neural Network training" /><published>2025-05-23T18:30:00+00:00</published> <updated>2025-05-23T18:30:00+00:00</updated> <id>https://pulkit1704.github.io//posts/deep-learning-mechanics/</id> <content type="text/html" src="https://pulkit1704.github.io//posts/deep-learning-mechanics/" /> <author> <name>Pulkit</name> </author> <summary>Peering into the Black Box: Various Perspectives to Neural Network training The field of Deep learning tries to model highly complex and non-linear functions to represent data using large and complex neural networks. The field has grown rapidly in popularity in recent years because of the enormous success of various Large Language Models like OpenAI ChatGPT, Google Gemini, Anthropics Claude. T...</summary> </entry> </feed>
