Learn how to enrich classic machine learning models with LLM-generated embeddings using seven practical, advanced feature engineering patterns for text.
Author Archive | Iván Palomares Carrascosa
10 Python One-Liners for Generating Time Series Features
10 simple Python one-liners for generating time series features based on different characteristics and properties underlying raw time series data
5 Advanced Feature Engineering Techniques with LLMs for Tabular Data
In this article, you will learn practical, advanced ways to use large language models to engineer features that fuse structured (tabular) data with text for stronger downstream models.
7 Feature Engineering Tricks for Text Data
From messy, raw text to clean, fully structured data features for AI and machine learning models: these simple tricks are all it takes.
7 Pandas Tricks to Handle Large Datasets
7 tricks that are often overlooked but are simple and effective to implement when using Pandas library to manage large datasets more efficiently, from loading to processing and storing data optimally.
Is ChatGPT-5 Able to Provide Proofs for Advanced Mathematics?
In this article, you will learn how GPT-5 handles intermediate to advanced mathematical reasoning, including solving systems of equations and constructing clean, textbook-style proofs.
A Decision Matrix for Time Series Forecasting Models
Why the choice of the right time series forecasting model matters, depending on data complexity, temporal patterns, and dimensionality.
7 Python Decorator Tricks to Write Cleaner Code
This article lists seven decorator tricks that can help you write cleaner code. Some of the examples shown are a perfect fit for using them in data science and data analysis workflows.
A Hands-On Introduction to cuML for GPU-Accelerated Machine Learning Workflows
In this article, you will learn what cuML is, and how it can significantly speed up the training of machine learning models through GPU acceleration.
A Hands-On Introduction to cuDF for GPU-Accelerated Data Workflows
In this article, you will learn what cuDF is and how to use it in a pandas-like way to accelerate common data-wrangling tasks on the GPU via a short, hands-on example.