#359: Lifecycle of a machine learning project

#359: Lifecycle of a machine learning project

Are you working on or considering a machine learning project? On this episode, we'll meet three people from the MLOps community: Demetrios Brinkmann, Kate Kuznecova, and Vishnu Rachakonda. They are here to tell us about the lifecycle of a machine learning project. We'll talk about getting started with prototypes and choosing frameworks, the development process, and finally moving into deployment and production.

Episoder(543)

#512: Building a JIT Compiler for CPython

#512: Building a JIT Compiler for CPython

Do you like to dive into the details and intricacies of how Python executes and how we can optimize it? Well, do I have an episode for you. We welcome back Brandt Bucher to give us an update on the up...

2 Jul 20251h 8min

#511: From Notebooks to Production Data Science Systems

#511: From Notebooks to Production Data Science Systems

If you're doing data science and have mostly spent your time doing exploratory or just local development, this could be the episode for you. We are joined by Catherine Nelson to discuss techniques and...

25 Jun 202554min

#510: 10 Polars Tools and Techniques To Level Up Your Data Science

#510: 10 Polars Tools and Techniques To Level Up Your Data Science

Are you using Polars for your data science work? Maybe you've been sticking with the tried-and-true Pandas? There are many benefits to Polars directly of course. But you might not be aware of all the ...

18 Jun 20251h 2min

#509: GPU Programming in Pure Python

#509: GPU Programming in Pure Python

If you're looking to leverage the insane power of modern GPUs for data science and ML, you might think you'll need to use some low-level programming language such as C++. But the folks over at NVIDIA ...

11 Jun 202557min

#508: Program Your Own Computer with Python

#508: Program Your Own Computer with Python

If you've heard the phrase "Automate the boring things" for Python, this episode starts with that idea and takes it to another level. We have Glyph back on the podcast to talk about "Programming YOUR ...

6 Jun 20251h 11min

#507: Agentic AI Workflows with LangGraph

#507: Agentic AI Workflows with LangGraph

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 l...

2 Jun 20251h 3min

#506: ty: Astral's New Type Checker (Formerly Red-Knot)

#506: ty: Astral's New Type Checker (Formerly Red-Knot)

The folks over at Astral have made some big-time impacts in the Python space with uv and ruff. They are back with another amazing project named ty. You may have known it as Red-Knot. But it's coming u...

19 Mai 20251h 4min

#505: t-strings in Python (PEP 750)

#505: t-strings in Python (PEP 750)

Python has many string formatting styles which have been added to the language over the years. Early Python used the % operator to injected formatted values into strings. And we have string.format() w...

13 Mai 20251h 11min

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