Intro Guide Mastering the art of storytelling is important for data scientists, but especially crucial for data analysts. Sharing the data insights and highlights with people unfamiliar with it, who may not even come from a technical background, is one of- 28390Murphy2025-03-23
Weather influences human decision making in ways from the obvious to the subtle and unexpected.- 25377Murphy2025-03-23
Learn about embeddings and agents to build a QA application- 20582Murphy2025-03-23
Fitbit activity analysis with DuckDB- 25616Murphy2025-03-23
Unpacking the data-centric AI concepts used in Segment Anything, the first foundation model for image segmentation- 25309Murphy2025-03-23
Fueling fear is a dangerous game- 29299Murphy2025-03-23
With examples and R codes- 29452Murphy2025-03-23
An exploration into the key differences between confidence and prediction intervals- 27752Murphy2025-03-23
Data preparation is famously the least-loved aspect of Data Science. If done right, however, it needn’t be such a headache. While scikit-learn has fallen out of vogue as a modelling library in recent years given the meteoric rise of PyTorch, LightGB- 29999Murphy2025-03-23
In our last blog post, we explored the Reinforcement Learning paradigm, delving into its core concepts of finite Markov Decision Processes, Policies, and Value Functions. Now, we are ready to apply our newfound knowledge and discover an alternative approa- 29528Murphy2025-03-23
This article was originally published on GPTech. When ChatGPT was first released in late 2022, its capabilities were simultaneously impressive and unimpressive. It could rap battle and write differential equations in LaTeX but didn’t know anything a- 26026Murphy2025-03-23
An end-to-end machine learning project inspired by the Data Mining the Water Table Competition- 27694Murphy2025-03-23
And try to analyze and develop models using these climate change datasets- 22172Murphy2025-03-23
Data Science Photo by Elena Mozhvilo on Unsplash Table of Contents · Initialize a Repository · Migrate Your Codebase ∘ config/config.py ∘ config/args.json ∘ tagolym/utils.py ∘ tagolym/data.py ∘ tagolym/train.py ∘ tagolym/predict.py ∘ tagolym/evaluate.py ∘- 27064Murphy2025-03-23
While low-dimensional datasets may seem of limited use, there are often ways to extract more features from them – especially if the dataset includes time data. Extracting additional features by "unpacking" a value for date and time can pro- 21465Murphy2025-03-23
Machine Learning and Artificial Intelligence are now being used in a tremendous number of fields, but with this increased use comes increased risks and ethical tests that models need to pass. Let’s take a motivating example with the recent news of a- 26136Murphy2025-03-23
In-depth explanation of the Naive Bayes family of classifiers, including a text classification example in Python- 20928Murphy2025-03-23
Temporary variables can make code clearer. What about the performance of such code?- 20349Murphy2025-03-23
A Guide to Text Generation From Beam Search to Nucleus Sampling- 24520Murphy2025-03-23
A values-based approach to program choice and networking.- 26583Murphy2025-03-23
Why is ChatGPT only trained up until 2021?
Learn how to rearrange your code to achieve significant speed improvements.
