AI/ML Research

7 Concepts Behind Large Language Models Explained in 7 Minutes

If you've been using large language models like GPT-4 or Claude, you've probably wondered how they can write actually usable…

4 months ago

Interpolation in Positional Encodings and Using YaRN for Larger Context Window

This post is divided into three parts; they are: • Interpolation and Extrapolation in Sinusoidal Encodings and RoPE • Interpolation…

4 months ago

How to Combine Scikit-learn, CatBoost, and SHAP for Explainable Tree Models

Machine learning workflows often involve a delicate balance: you want models that perform exceptionally well, but you also need to…

4 months ago

Positional Encodings in Transformer Models

This post is divided into five parts; they are: • Understanding Positional Encodings • Sinusoidal Positional Encodings • Learned Positional…

4 months ago

Navigating Imbalanced Datasets with Pandas and Scikit-learn

Imbalanced datasets, where a majority of the data samples belong to one class and the remaining minority belong to others,…

5 months ago

Step-by-Step Guide to Deploying Machine Learning Models with FastAPI and Docker

You've trained your machine learning model, and it's performing great on test data.

5 months ago

Implementing Vector Search from Scratch: A Step-by-Step Tutorial

There’s no doubt that search is one of the most fundamental problems in computing.

5 months ago

How to Optimize Language Model Size for Deployment

The rise of language models, and more specifically large language models (LLMs), has been of such a magnitude that it…

5 months ago

Dealing with Missing Data Strategically: Advanced Imputation Techniques in Pandas and Scikit-learn

Missing values appear more often than not in many real-world datasets.

5 months ago