Engineering Best Practices
Quantization: Optimize ML Models to Run Them on Tiny Hardware
A must-know skill for ML engineers to reduce model footprint and inference time.
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Engineering Best Practices
How to Structure Your Code for Machine Learning Development
A highly overlooked yet critical skill for data scientists.
Engineering Best Practices
Develop an Elegant Testing Framework For Data Science Projects Using Pytest
A Comprehensive Guide to Pytest for data scientists.
Engineering Best Practices
A Beginner-friendly Guide to Multi-GPU Model Training
Models are becoming bigger and bigger. Learn how to scale models using distributed training.
Engineering Best Practices
Object-Oriented Programming with Python for Data Scientists
A beginner to advanced guide for Python OOP.
Engineering Best Practices
11 Powerful Techniques To Supercharge Your ML Models
Take your ML models to the next level with 11 lesser-known techniques.
Classical ML and Deep Learning
Implementing KANs From Scratch Using PyTorch
A step-by-step demonstration of an emerging neural network architecture — KANs.
Classical ML and Deep Learning
A Beginner-friendly Introduction to Kolmogorov Arnold Networks (KAN)
What are KANs, how are they trained, and what makes them so powerful?
