MLG 010 Languages & Frameworks

The 2025 generative AI image market is a trade-off between aesthetic quality, instruction-following, and user control. This episode analyzes the key platforms, comparing Midjourney's artistic output against the superior text generation and prompt adherence of GPT-4o and Imagen 4, ... Show More

Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Advanced auto encoder types, such as denoising, sparse, and variational auto encod ... Show More

At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation (RAG) by embedding documents into vector databases for real-time factual lookup ... Show More

In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly. To make a comparison with the Python ecosystem I wi ... Show More

Jordan Adler is Head of Developer Engineering at OneSignal and has a deep interest in code generation. He has helped migrate large systems from Python 2 or Python 3 using code generation and code transformation. Using tools like Yellicode, Python Future, and others, Jordan's team ... Show More

Wolf Vollprecht, the CEO and founder of Prefix.dev, speaks with host Gregory M. Kapfhammer about how to implement Python tools, such as package managers, in the Rust programming language. They discuss the challenges associated with building Python infrastructure tooling in Python ... Show More

Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's ... Show More

Let's say you want to create a web app and you know Python really well. Your first thought might be Flask or Django or even FastAPI? All good choices but there is a lot to get a full web app into production. The framework we'll talk about today, Reflex, allows you to just write P ... Show More

Join me for an insightful conversation with Alex Monahan, who works on documentation, tutorials, and training at DuckDB Labs. We explore why DuckDB is gaining momentum among Python and data enthusiasts, from its in-process database design to its blazingly fast, columnar architect ... Show More

Wrangling data in Pandas, when to use Pandas, Matplotlib or Seaborn, and why you should learn to create Python packages: Jon Krohn speaks with guest Stefanie Molin, author of Hands-On Data Analysis with Pandas.This episode is brought to you by Posit, the open-source data science ... Show More

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 l ... Show More

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Science Notebooks, Jupyter, Colab, explain how these terms relate to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and C ... Show More

You're about to launch your new app or API, or even just a big refactor of your current project. Will it stand up and deliver when you put it into production or when that big promotion goes live? Or will it wither and collapse? How would you know? Well you would test that of cour ... Show More