In our final talk of the night, Yash Kamothi briefly introduces the architecture and development process of Sentry. Then, we turn to the practices Sentry follows to improve the overall experience of developing the Sentry codebase. Connect with Yash here: yash.kamothi at sentry dot io Google AIPs...

   In our second talk of the night, Lisa Dusseault covers the nuances of various approaches to data processing with Python, their pros, cons, and specializations. Connect with Lisa here: https: mastodon.geekery.org lisarue Check out phaser here: https: github.com lisad phaser For more details...

   In the first talk of the night, James Abel talks us through some of the history, realities, and pitfalls of handling spreadsheets with python. Find the slides here: https: github.com jamesabel spreadsheetdoeswhat Get connected with James here: https: www.abel.co For more details about SF...

   In the first talk of the night, Dash takes us on a journey through the intricacies of cutting edge technologies such as PyTorch, OpenAI, Streamlit, Snowflake, and more. Connect with Dash here: https: www.linkedin.com in dash desai For more details about SF Python and to speak attend future...

   In our final talk of the night, Jon aka darakian takes us through how GitHub’s Dependabot works with and for the community to secure the world and also Python Jon is a security analyst working in the Security Lab at GitHub. He is primarily concerned with maintaining the breadth and quality of...

   In the second talk of the night, Christopher guides us through the transformative technology journey at The RealReal TRR , where he co invented a patented AI system to revolutionize photo retouching with Python. With TRR processing k items each day, capturing images per item, the...

   Jessica Temporal https: pybay.com speakers sz speaker a d e c c e c JSON Web Tokens, or JWTs for short, are all over the web. They can be used to track bits of information about a user in a very compact way and can be used in APIs for authorization purposes. Join me and...

   Tuana Celik https: pybay.com speakers sz speaker bf d fa c a d Retrieval augmented generation has proven to be quite an effective technique to achieve good results with LLMs, so that they may provide answers based on your own data. ; ; While retrieval is a key step...

   Mayank Jindal https: pybay.com speakers sz speaker ec de b b fd f b In recent years, serverless computing has brought about a paradigm shift in the realm of software development and deployment. This transformation has not only revolutionized application construction but has...

   Chris Brousseau https: pybay.com speakers sz speaker b b f f d b b d a Supercharge your data engineering workflows by merging the robustness of Pandas with the high speed capabilities of Polars, all underpinned by Apache Arrow’s in memory technology. This technical deep dive...

   Lizzie Siegle https: pybay.com speakers sz speaker cefe f aeca c ad d f f ecce a With LangChain, developers ldquo;chain rdquo; together different LLM components to create more advanced use cases around LLMs. Agents use LLMs to decide what actions should be taken. Get introduced to...

   Jason Koo https: pybay.com speakers sz speaker e d ae b f b c c Existing mock data generators can only create individual, unrelated tables of fake data. Synthetic data services that can produce interwoven datasets require real data to anonymize. This leaves only error prone...

   Simon Willison https: pybay.com speakers sz speaker b e eb b acd e ba ce c Embeddings are a Large Language Model adjacent technology that allow data such as text or images to be represented as an array of floating point numbers, representing a location in a weird, multi...

   Adrian Garcia Badaracco https: pybay.com speakers sz speaker c c e d a c ba This talk will introduce Pydantic users, old or new, to the new APIs available in Pydantic v , best practices for using them, and some of the powerful new features we added support for, like PEP...

   Grishma Jena https: pybay.com speakers sz speaker e f fbea cf af aba abc The nature of the field of Data Science encourages trial and error, but we can do a better job of destigmatizing failure and learn from our collective experiences. Join me as I take us on an adventure to find...