#503: The PyArrow Revolution

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Everyday AI Podcast – An AI and ChatGPT Podcast

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Ep 563: ChatGPT's New Custom GPT's: Advanced techniques to win back time 46:43

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Think you know ChatGPT's custom GPTs? 🤔 Probably not. Last week, we tackled the basics and what's new with OpenAI's refreshed GPTs. For this AI Working Wednesdays episode, we're getting into some advanced techniques to hep you win back time. ↳ using the crazy powerful o3 model to your GPT's advantage ↳ context stacking ↳ custom actions to connect to third party sites Yeah.... don't sleep on this one shorties. Ep 563: ChatGPT's New Custom GPT's: Advanced techniques to win back time Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Join the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Custom GPTs: Advanced Techniques Overview OpenAI's Context Stacking Strategy O3 Model's Thinking Capabilities Building Efficient Custom GPTs Custom Actions and API Integration Zapier Integration for Dynamic Data ChatGPT's Context Window Management Creating Evergreen Podcast Content Timestamps: 00:00 Custom GPTs: Evolution and Insights 03:23 "Mastering GPT Context Stacking" 09:31 "Context Stacking in Chat GPT" 11:20 GPT Context Switching Advantage 15:33 Customizable GPT Usage Explained 19:51 Evergreen Episode Update Strategy 21:44 Optimizing AI for Continued Learning 23:48 "O-Series Models: Advanced AI Capabilities" 28:41 Building GPTs for Episode Research 30:03 GPT Model Customization and Sharing 33:18 Securing API Keys in GPTs 36:55 Zapier Enhances GPT Email Capabilities 42:12 "Use Chrome Extensions for Tokens" 43:48 "AI at Work Wednesdays Survey" Keywords: OpenAI's custom GPTs, advanced techniques, save time, context stacking, o three model, ChatGPT updates, logic and reasoning, plan ahead capabilities, agentic tools, custom actions, third party data, API, building GPTs, leveraging AI, context window, transformer model, generative AI, organization usage, fine tuning performance, productivity enhancement, AI agents, AI tools integration, custom configuration, everyday applications, tech strategies, new rendition, midweek break, AI experts, smarter AI usage, AI-powered planning, AI transformations. Ep 563: ChatGPT's New Custom GPT's: Advanced techniques to win back time Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner…

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Pandas is at a the core of virtually all data science done in Python, that is virtually all data science. Since it's beginning, Pandas has been based upon numpy. But changes are afoot to update those internals and you can now optionally use PyArrow. PyArrow comes with a ton of benefits including it's columnar format which makes answering analytical questions faster, support for a range of high performance file formats, inter-machine data streaming, faster file IO and more. Reuven Lerner is here to give us the low-down on the PyArrow revolution.
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Talk Python Courses

Links from the show

Reuven: github.com/reuven
Apache Arrow: github.com
Parquet: parquet.apache.org
Feather format: arrow.apache.org
Python Workout Book (45% off with code talkpython45): manning.com
Pandas Workout Book (45% off with code talkpython45): manning.com
Pandas: pandas.pydata.org
PyArrow CSV docs: arrow.apache.org
Future string inference in Pandas: pandas.pydata.org
Pandas NA/nullable dtypes: pandas.pydata.org
Pandas `.iloc` indexing: pandas.pydata.org
DuckDB: duckdb.org
Pandas user guide: pandas.pydata.org
Pandas GitHub issues: github.com
Watch this episode on YouTube: youtube.com
Episode #503 deep-dive: talkpython.fm/503
Episode transcripts: talkpython.fm
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