Course content
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Code Quality & Project Structurex Lessons
- 8 Fatal (Yet Non-obvious) Pitfalls and Cautionary Measures in Data Science
- 11 Powerful Techniques To Supercharge Your ML Models
- Object-Oriented Programming with Python for Data Scientists
- Develop an Elegant Testing Framework For Data Science Projects Using Pytest
- How to Structure Your Code for Machine Learning Development
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Experiment Tracking & Version Controlx Lessons
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Model Deployment & Optimizationx Lessons
- Sklearn Models are Not Deployment Friendly! Supercharge Them With Tensor Computations.
- PyTorch Models Are Not Deployment-Friendly! Supercharge Them With TorchScript.
- Deploy, Version Control, and Manage ML Models Right From Your Jupyter Notebook with Modelbit
- Model Compression: A Critical Step Towards Efficient Machine Learning
- Quantization: Optimize ML Models to Run Them on Tiny Hardware
- 5 Must-Know Ways to Test ML Models in Production (Implementation Included)
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Scaling & Distributed Computingx Lessons
Published on May 30, 2025