The Easiest Way To Stay Up to Date With Machine Learning.

Author(s): Serop Baghdadlian

Originally published on Towards AI.

Read 10x more relevant articles by building the most efficient system for tracking and organizing machine learning & engineering articles.
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Have you ever felt that you’re not staying up to date with the latest innovations, architecture designs, and new tech in machine learning?

If your answer is no, then this article is not for you — congratulations! 🥳

However, if your answer is yes,

then I’m glad you found this article because I have a great trick for you!🤯

In this article, I will share a simple system that has helped me read nearly 10 times more articles per month, which has almost doubled my machine learning knowledge in a very short period.

Working in the data science industry is becoming increasingly challenging. Everything is moving so fast, and we are expected to stay up to date with the latest tech and methods, from LLMs and RAG applications to deployment strategies.

In the generative AI space, tech that was created one year ago seems outdated today. If you leave frameworks for six months, you’ll need to get onboarded again because so many things have changed.

Best practices and services are constantly evolving (like replacing Kubeflow with Vertex AI on the Google Cloud Platform).

The job market continuously demands new skills for hiring, and it’s a race to keep up. Currently, jobs related to LLMs… Read the full blog for free on Medium.

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Published via Towards AI