Apr

With interest rates continuing to rise, 0% APR car financing deals are getting pretty hard to find. It’s much more likely that you’ll find deals between 2 and 5% which, obviously, isn’t as good a deal as previously famous 0% offers. There are a few 0.99% deals around but who even wants to pay that, right? If you’re looking to buy a new car, you want to get a great financing deal. While 0% deals may be less widespread, we’ve still found a few that are worth checking out. Take a look below at what we’ve picked out.…

Here’s a breakdown of the logic for creating a custom function:1. Start with creating one visual first2. Understand which variable you want to use to create multiple plots3. Change the graphing code into a function4. Loop through your unique values to generate multiple plotsLet’s work with the adorable Palmer Penguins dataset from Allison Horst. This dataset has three unique species of penguins — Chinstrap, Gentoo, Adelie:Artwork by @allison_horstHere’s how to load the data# Load…

Using DMV Data with Pandas and GeoPandasTesla (Courtesy of Matt Weissinger on pexels.com)California is pushing for aggressive societal change towards a net-zero emissions future, and a big piece of that puzzle are the vehicles its citizens use to go about their daily lives. In conjunction with the Inflation Reduction Act (which provides tax credits up to $7,500 for new EV purchases and up to $4,000 for used EVs — conditional on locations of vehicle assembly and battery material sourcing), California has implemented the…

Machine learning has undoubtedly become a powerful tool in today’s data-driven world, but are we truly tapping into its full potential? Traditional evaluation metrics like accuracy, precision, and recall have long held the spotlight, but there’s so much more to consider when measuring a model’s real-world impact. In this article, we’ll dive into the lesser-known, unconventional metrics that are reshaping the way we assess machine learning models. From fairness, privacy and calibration, to enery consumption, data…

Some supervised, some unsupervised, some self-supervised, in NLP and computer visionImage by Gerd Altmann From PixabaySingle-task learning is the process of learning to predict a single outcome (binary, multi-class, or continuous) from a labeled data set.By contrast, multi-task learning is the process of jointly learning to predict multiple outcomes on inputs of the same modality. Such as images or text.The obvious question to ask is, why learn jointly? Why not independently learn single-task models to predict the various…

A hands-on guide on building a web application to deploy your forecasting model using PythonPhoto by SpaceX on UnsplashAs data scientists, we often work in the experimentation phase. We work in notebooks and develop scripts to evaluate models, and it stops there.However, our work is never really done until the model is deployed. This crucial step brings us new challenges, as we have to think about error handling, and building an interface to interact with the model.This is where Streamlit comes in: it is a Python library…

Making Data UsefulHow to muscle up on data-related topics quickly(Feeling impatient? Scroll past the text and cat photo to get the learning paths!)Your author.First, may I say a huge thank you to all of you for encouraging me to write? I just noticed that here on Medium, my community of followers is 70% the size of Barack Obama’s. Whoa!I’m honored and humbled by all the love this amazing community has given me. I don’t know if it’s despite my being a cheerful weirdo or because of it, but thank you! And thank you for being…

Discover the Hidden Benefits and Drawbacks of dbtImage by AuthorIf your organization is looking to create a data-driven product, you should consider having efficient data pipelines to:Stay competitive: Quick access to data and its analysis through efficient data pipelines accelerates decision-making and keeps you ahead of your competition.Reduce costs: The time and effort required to collect and transform data can be significantly reduced with efficient data pipelines, which can reduce costs and enable employees to focus…

A high quality digital art view of a robot in the centre, who is able to do technical coding, write amazing prose and do strategic thinking (author created, with DALL-E).Data analysis can be equal parts challenging and rewarding. From cleaning messy datasets to building complex models, there’s always a lot to do, and not enough time to do it. But what if there was a way to streamline and automate some of the more routine tasks, freeing up more time for strategic thinking and decision-making? That’s where LLMs come in.LLMs…

RL meets hyperbolic geometryMany problems in Reinforcement Learning manifest a hierarchical tree-like nature. Hyperbolic spaces, which can be conceptualised as continuous analogies of trees, are thus suitable candidates to parameterise the agent’s deep model. In this post, we overview the basics of hyperbolic geometry, show empirically that it provides a good inductive bias for many RL problems, and describe a practical regularisation procedure allowing to resolve numerical instabilities in end-to-end optimisation with…