If you want to leverage the power of LLMs in your Python apps, you would be wise to consider an agentic framework. Agentic empowers the LLMs to use tools and take further action based on what it has learned at that point. And frameworks provide all the necessary building blocks to weave these into your apps with features like long-term memory and durable res ... 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 2021
002. Financial instruments’ variety
<p>In this episode, we explore the diverse world of financial instruments, examining the various types available for investors and traders alike. From traditional assets like stocks and bonds to alternative options such as derivatives and commodities, we discuss how each instrume ... Show More
3m 28s
May 2022
009. Cash Statement and How it Links to Other Statements
<p>In this episode, we explore the cash statement, also known as the cash flow statement, and its critical role in financial reporting. We break down the three main sections—operating, investing, and financing activities—and explain how they provide insights into a company’s liqu ... Show More
7m 12s