Have you ever wondered why certain data points stand out so dramatically? They might hold the key to everything from fraud detection to groundbreaking discoveries. This week on Talk Python to Me, we dive into the world of outlier detection with Python with Brett Kennedy. You'll learn how outliers can signal errors, highlight novel insights, or even reveal hi ... Show More
Nov 10
#527: MCP Servers for Python Devs
Today we’re digging into the Model Context Protocol, or MCP. Think LSP for AI: build a small Python service once and your tools and data show up across editors and agents like VS Code, Claude Code, and more. My guest, Den Delimarsky from Microsoft, helps build this space and will ... Show More
1h 6m
Nov 1
#526: Building Data Science with Foundation LLM Models
Today, we’re talking about building real AI products with foundation models. Not toy demos, not vibes. We’ll get into the boring dashboards that save launches, evals that change your mind, and the shift from analyst to AI app builder. Our guide is Hugo Bowne-Anderson, educator, p ... Show More
1h 7m
Nov 2016
Python, Django, and Channels (Interview)
Django core contributor Andrew Godwin joins the show to tell us all about Python and Django. If you've ever wondered why people love Python, what Django's virtues are as a web framework, or how Django Channels measure up to Phoenix's Channels and Rails' Action Cable, this is the ... Show More
1h 15m
Jun 2018
Python at Microsoft (Interview)
We talked with Steve Dower and Dan Taylor at Microsoft Build 2018 about the history of Python at Microsoft, the origination of IronPython, Python Tools for Visual Studio, flying under the radar to add support Python, fighting from within to support open source, and more.
37m 51s
Apr 2025
AGI is still 30 years away — Ege Erdil & Tamay Besiroglu
Ege Erdil and Tamay Besiroglu have 2045+ timelines, think the whole "alignment" framing is wrong, don't think an intelligence explosion is plausible, but are convinced we'll see explosive economic growth (economy literally doubling every year or two).This discussion offers a tota ... Show More
3h 8m
Oct 13
Evals, error analysis, and better prompts: A systematic approach to improving your AI products | Hamel Husain (ML engineer)
Hamel Husain, an AI consultant and educator, shares his systematic approach to improving AI product quality through error analysis, evaluation frameworks, and prompt engineering. In this episode, he demonstrates how product teams can move beyond “vibe checking” their AI systems t ... Show More
54m 48s
Feb 2025
MATLAB vs. Python vs. Julia: The Hidden Truths - Gareth Thomas | Podcast #147
🌎 More about Versionbay: https://www.versionbay.com/Connect with Gareth on LinkedIn: https://www.linkedin.com/in/g-thomas/In this episode, we sit down with Gareth Thomas, founder of VersionBay, to explore the critical role of software versioning in engineering and how companies ... Show More
32m 57s