Engineering Best Practices
Deploy, Version Control, and Manage ML Models Right From Your Jupyter Notebook with Modelbit
Deployment has possibly never been so simple.
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Engineering Best Practices
PyTorch Models Are Not Deployment-Friendly! Supercharge Them With TorchScript.
Eliminating the dependence of PyTorch models on Python.
Engineering Best Practices
Optimize Your ML Development and Operations with MLflow
The guide that every data scientist must read to manage ML experiments like a pro.
Engineering Best Practices
How to Streamline Your Machine Learning Workflow With DVC
The guide that every data scientist must read to manage ML experiments like a pro.
Engineering Best Practices
You Cannot Build Large Data Projects Until You Learn Data Version Control!
The underappreciated, yet critical, skill that most data scientists overlook.
Classical ML and Deep Learning
A Mathematical Deep Dive Into the Curse of Dimensionality
Mathematically understanding the surprising phenomena that arise when dealing with data in high dimensions.
Classical ML and Deep Learning
Why Bagging is So Ridiculously Effective At Variance Reduction?
Diving into the mathematical motivation for using bagging.
Engineering Best Practices
Sklearn Models are Not Deployment Friendly! Supercharge Them With Tensor Computations.
Speed up sklearn model inference up to 50x with GPU support.
