Joined October 2016
- Tweets 63,328
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- Followers 250,482
- Likes 7,904
1,700 Photos and videos
Interested in the emerging field of quantum machine learning?
Don't miss Davinder Singh's new article, which explains how errors arise in classical and quantum systems, why quantum information is fundamentally fragile, and much more. towardsdatascience.com/how-t…
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Interested in integrating the power of LLMs into your recommender systems? Piero Paialunga explains how you can improve precision along the way, too. towardsdatascience.com/incre…
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Agents require more than just model weights and an API server. Hussen Mohammed Ibrahim breaks down the systems needed to support long-context reasoning and tool use locally.
towardsdatascience.com/the-i…
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ETL sounds complex until you actually build one from scratch. @IbrahimHabibEg explains the step-by-step process of extracting, transforming, and loading data as a beginner.
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If you're interested in Python, SLM fine-tuning, and/or emotion recognition, @PetrKorab presents a new, accessible tutorial based on the Mistral Small 3.1 model and a social media-based dataset. towardsdatascience.com/how-t…
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Interested in automating your prompt-creation workflow? Don't miss W Brett Kennedy's new guide, which leverages DSPy to save practitioners time and effort. towardsdatascience.com/autom…
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Learn how Azure Layout can be used when your RAG workflow requires more advanced, scalable PDF parsing — Kezhan Shi goes into the details in the latest article in the Enterprise Document Intelligence series. towardsdatascience.com/when-…
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"We’ve seen a massive shift from convolutional networks to the new Transformer architectures that power today’s [LLMs], but the way these networks route information from one layer to another hasn’t changed all that much."
@SteadySurdom explores new research that aims to address this status quo. towardsdatascience.com/why-t…
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Follow along as @ibbysalam continues his journey into the nitty-gritty execution details of data engineering. His new article focuses on ETL pipeline pain points. towardsdatascience.com/i-tho…
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A story about a broken printer inspired Shuyang to dig into a much bigger and more consequential question: is language primarily a visual system from the perspective of a language model? towardsdatascience.com/is-la…
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For his latest technical deep dive, Chien Vu Minh takes a detailed look at Claude's new ability to write its own, task-specific harnesses on the fly. towardsdatascience.com/a-har…
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Towards Data Science retweeted
Jun 12
The second part of my beginner's guide to PySpark just dropped on @TDataScience . In it, we take your skills to the next level by discussing performant data handling.
Read it for free using the link below,
towardsdatascience.com/pyspa…
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"Should an agent learn only from the behavior it is currently using, or can it also learn from behavior generated in some other way?"
Ananya Bhattacharyya explains why this choice has far-reaching implications around exploration, safety, and efficiency. towardsdatascience.com/the-f…
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Tired of continuously copy-and-pasting files into an AI chat window, @emmimalpa came up with a robust pipeline that leverages a zero-dependency MCP server to give AI tools the access they need. towardsdatascience.com/my-ai…
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"For the first time, the capacity to ask questions, explore data, and surface answers is no longer tied to how many analysts you can hire or how many dashboards you can build."
Mahdi Karabiben unpacks the changes agentic AI is bringing to the field of business intelligence. towardsdatascience.com/bi-is…
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For the latest article in their enterprise document intelligence series, Kezhan Shi and Angela Shi zoom in on the nitty-gritty details of parsing a PDF file. towardsdatascience.com/stop-…
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Ready to take your PySpark knowledge to the next level? Don't miss @taupirho's new guide, which shows how to build real workflows with Spark on your laptop. towardsdatascience.com/pyspa…
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If you're trying to get a sense of how close to full capacity your GPUs actually are, Arjun Kaarat warns against over-relying on any "average utilization" metric. towardsdatascience.com/when-…
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In a detailed, hands-on comparison, Yan Georget takes a close and nuanced look at two very different constraint solvers: tried-and-tested Choco, and his own open source project, NuCS. towardsdatascience.com/nucs-…
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Isn't it time we unify our AI workflows into a cohesive, streamlined experience?
Manu R. (Thanks to @abacusai) explains why things got so complicated — and how we can move forward into a more productive future. towardsdatascience.com/how-t…
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