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.
DBSCAN++: The Faster and Scalable Alternative to DBSCAN Clustering
Addressing major limitations of the most popular density-based clustering algorithm — DBSCAN.
8 Classic Alternatives to Traditional Plots
...that every Data Scientist must add in their visualisation toolkit.
Federated Learning: A Critical Step Towards Privacy-Preserving Machine Learning
Learn real-world ML model development with a primary focus on data privacy – A practical guide.
How to (Massively) Streamline Your Machine Learning Workflow With DVC
The guide that every data scientist must read to manage ML experiments like a pro.
You Cannot Build Large Data Projects Until You Learn Data Version Control!
The underappreciated, yet critical, skill that most data scientists overlook.
Why Bagging is So Ridiculously Effective At Variance Reduction?
Diving into the mathematical motivation for using bagging.
Sklearn Models are Not Deployment Friendly! Supercharge Them With Tensor Computations.
Speed up sklearn model inference up to 50x with GPU support.
