Augmenting LLMs: Fine-Tuning or RAG?
Understanding the tradeoffs between RAG and Fine-tuning, and owning the model vs. using a third-party host.
Daily Dose of Data Science
Every week, we share practical no-fluff deep dives on topics that truly matter to your skills for succeeding and staying relevant in ML & DS roles.
Implementing LoRA From Scratch for Fine-tuning LLMs
Understanding the challenges of traditional fine-tuning and addressing them with LoRA.
A Beginner-friendly and Comprehensive Deep Dive on Vector Databases
Understanding every little detail on vector databases and their utility in LLMs, along with a hands-on demo.
You Are Probably Building Inconsistent Classification Models Without Even Realizing
The limitations of always using cross-entropy loss in ordinal datasets.
PyTorch Models Are Not Deployment-Friendly! Supercharge Them With TorchScript.
Eliminating the dependence of PyTorch models on Python.
How To (Immensely) Optimize Your Machine Learning Development and Operations with MLflow
The guide that every data scientist must read to manage ML experiments like a pro.
Don't Stop at Pandas and Sklearn! Get Started with Spark DataFrames and Big Data ML using PySpark
A completely hands-on and beginner-friendly deep dive on PySpark using Databricks.
