Hosted by probabl · 🇺🇸 US · EN · 14 episodes
Established thought leaders with verified media credentials.
Sample space is a podcast about tools, thoughts and techniques from machine learning practitioners. We talk to toolmakers and practitioners about interesting problems in the real world to find out how great ideas in our field actually manifest.
probabl hosts Sample Space, a technology show with 14 episodes published.
Word embeddings might feel like they are a little bit out of fashion. After all, we have attention mechanisms and transformer models now, right? Well, it turns out that if you apply distillation the right way you can act
Imbalanced learn is one of the most popular scikit-learn projects out there. It has support for resampling techniques which historically have always been used for imbalanced classification use-cases. However, now that we
There are many LLMs that you can use for programming these days. Some of them even go into your IDE like Cursor or Github Copilot. But what if you want to tweak these LLMs do to what you want? Instead of being stuck with
Scikit-learn's documentation pages are celebrated. But not everyone is aware that the project actually has somebody on payroll to take care of it. In this episode we talk to Arturo about stories from the scikit-learn doc
Vector databases are kind of everywhere these days. There is a big pool of VC's that are pooring money into the ecosystem too. But while all of that is happening, sqlite has also gotten support for it. In this episode we
Jupyter has been a great environment to explore computational ideas, but that doesn't mean that it can be the only environment for interactive coding in Python. It also comes with some downsides, which led Akshay Agrawal
When you are working on a data pipeline for ML ... you are never dealing with a single table. It always demands different tables for different reasons that all have to be mashed together in order to have something that y
When you pip install a package you will for sure end up using it later. But often you will also install a bunch of dependencies and it is very likely that you won't directly interact with all of them. That does not mean
A lot of things can (and have) gone wrong when folks tried to apply data science projects. So how might we prevent that? Maybe what we need to do is to look at the medical profession and their practice of checklists befo
Historically it's always been the case that you would use a pickle file to store a trained scikit-learn model on disk for deployment. Pickles make sense because these are so flexible, but they do carry a security concern
Leland McInnes is known for a lot of packages. There's UMAP, but also PyNNDescent and HDBScan. Recently he's also been working on tools to help visualise clusters of data and he's also cooking up something new that's rel
Ibis is a Python library that offers a single data-frame API, from Python, which can run your queries on many different backends. These include databases like Postgres, but also commercial vendors like BigQuery and Snowf
In this (first!) episode of Sample Space we talk to Trevor Mantz, the creator of anywidget. It's a (neat!) tool to help you build more interactive notebooks by giving you tools to apply just enough Javascript to get dire
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Sample Space is hosted by probabl. The show is categorised under technology and has published 14 episodes.
Sample Space has published 14 episodes.
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