#pydatabos Jupyter extension popularity per category

#pydatabos closing us out! Talking about the Jupyter extension ecosystem

#pydatabos example open and performant "small" LLM - xLM model

#pydatabos better usage of small language models for complex "autonomous" tasks

#pydatabos a practical talk on how to process large files

#pydatabos how to involve domain experts in LLM pipelines

#pydatabos discussing inherent biases in data fueling ML

#pydatabos the famed Eric Ma on how to code with agents

#pydatabos use of anomaly detection in predictive maintenance

#pydatabos day 3! Foundational models for times series anomaly detection!

#pydatabos the boring loop underlying agentic AI

#pydata last talk of the day! Sebastian Walkotter on Gen AI apps

#pydatabos the inimitable @allendowney.bsky.social presenting a Bayesian mystery

#pydatabos more on developing metrics for data products

#pydatabos Our second keynote Lisa Amini talking about what's next in AI

#pydatabos boundary failure in LLMs - asking a car dealership chatbot to solve complex mathematics

#pydatabos types of failure in Gen AI

#pydatabos the issue with traditional ML metrics and the new Gen AI era with Rebecca Bilbro

#pydatabos foundational elements of Gen AI use at Vertex

#pydatabos separation between "analytical AI" and "Gen AI" in healthcare

#pydatabos session 2 kicking off with Lily Xu from Vertex on traditional ML and LLM in healthcare

#pydatabos pipeline management map

#pydatabos Dawn Wages taking us through building with Jupyter notebooks

#pydatabos Keynote speaker @isabellezimm.bsky.social on building open source tools

#pydatabos day 2!!

#pydatabos25 cool timeline auto complete to automation

#pydatabos25 generative programming with Mellea!

#pydatabos25 Eric Ma on building LLMs made simple!

#pydatabos25 building MCP servers

First up - notebook to pipeline with snowflake #pydatabos25

It begins! #pydatabos25

#pydatabos multiple ways to speed up your code - parallelism is just one!

#pydatabos love this - build damaging software, make damage more efficient

#pydatabos Itamar Turner-Trauring up next on optimizing your code!

#pydatabos where AI fits into the a family vacation planning workflow

#pydatabos back at it again! Tri Dang from Revspring Inc talking to us about building AI agents

#pydatabos one line motivation for using DSPy!

#pydatabos the main event! Omar Khattab on DSPy 3.0!

#pydatabos interesting! How the Arbor library works under the hood hand in hand with DSPy

#pydatabos introduction to Arbor library for optimizing weights along with the prompts

#pydatabos how prompt optimization works at Amazon Nova

#pydatabos on to prompt optimization - why do we need a tool like DSPy to optimize our prompts?

#pydatabos introducing retrieve-dspy building retrieval workflows alongside dspy

#pydatabos talking about compound retrieval systems with @weaviate.bsky.social

#pydatabos is back again! Thanks to @weaviate.bsky.social for putting together an awesome agenda on DSPy!

The smallest possible MCP server with FastMCP #pydatabos

Where do MCP tools live in an agent workflow #pydatabos

Next up from Sebastian Wallkötter on building with MCP servers #pydatabos

Overview of the story agent Emma is building #pydatabos

Emma Saroyan on building AI agents #pydatabos www.linkedin.com/in/emma-saro...