research

Zero-Shot and Few-Shot Classification with Scikit-LLM

In this article, you will learn: • how Scikit-LLM integrates large language models like OpenAI's GPT with the Scikit-learn framework…

3 months ago

Building a Plain Seq2Seq Model for Language Translation

This post is divided into five parts; they are: • Preparing the Dataset for Training • Implementing the Seq2Seq Model…

3 months ago

Synthetic Dataset Generation with Faker

In this article, you will learn: • how to use the Faker library in Python to generate various types of…

3 months ago

From Linear Regression to XGBoost: A Side-by-Side Performance Comparison

Regression is undoubtedly one of the most mainstream tasks machine learning models can address.

3 months ago

Feature Engineering with LLM Embeddings: Enhancing Scikit-learn Models

Large language model embeddings, or LLM embeddings, are a powerful approach to capturing semantically rich information in text and utilizing…

3 months ago

Revisiting k-Means: 3 Approaches to Make It Work Better

The k-means algorithm is a cornerstone of unsupervised machine learning, known for its simplicity and trusted for its efficiency in…

3 months ago

Discussing Decision Trees: What Makes a Good Split?

It’s no secret that most advanced artificial intelligence solutions today are predominantly based on impressively powerful and complex models like…

3 months ago

7 Pandas Tricks That Cut Your Data Prep Time in Half

Data preparation is one of the most time-consuming parts of any data science or analytics project, but it doesn't have…

3 months ago

Word Embeddings for Tabular Data Feature Engineering

It would be difficult to argue that word embeddings — dense vector representations of words — have not dramatically revolutionized…

3 months ago

Decision Trees Aren’t Just for Tabular Data

Versatile, interpretable, and effective for a variety of use cases, decision trees have been among the most well-established machine learning…

3 months ago