The Machine Learning Practitioner’s Guide to Fine-Tuning Language Models
Fine-tuning has become much more accessible in 2024–2025, with parameter-efficient methods letting even 70B+ parameter models run on consumer GPUs.
5 Advanced Feature Engineering Techniques with LLMs for Tabular Data
In the epoch of LLMs, it may seem like the most classical machine learning concepts, methods, and techniques like feature engineering are no longer in the spotlight.
7 Must-Know Agentic AI Design Patterns
Building AI agents that work in production requires more than powerful models.
Future-Proofing Your AI Engineering Career in 2026
AI engineering has shifted from a futuristic niche to one of the most in-demand tech careers on the planet.
The Complete Guide to Vector Databases for Machine Learning
Vector databases have become essential in most modern AI applications.
Revolutionizing MLOps: Enhanced BigQuery ML UI for Seamless Model Creation and Management
Exciting news for BigQuery ML (BQML) users.
3 Ways to Speed Up Model Training Without More GPUs
In this article, you will learn three proven ways to speed up model training by optimizing precision, memory, and data flow — without adding any…
7 Feature Engineering Tricks for Text Data
An increasing number of AI and machine learning-based systems feed on text data — language models are a notable example today.
10 Python One-Liners for Calling LLMs from Your Code
You don’t always need a heavy wrapper, a big client class, or dozens of lines of boilerplate to call a large language model.
7 Pandas Tricks to Handle Large Datasets
Large dataset handling in Python is not exempt from challenges like memory constraints and slow processing workflows.