Classical ML and Deep Learning
Graph Neural Networks Part 1 (Implementation Included)
A practical and beginner-friendly guide to building neural networks on graph data.
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Classical ML and Deep Learning
Model Calibration (Part 2)
How to make ML models reflect true probabilities in their predictions?
Classical ML and Deep Learning
Federated Learning: A Critical Step Towards Privacy-Preserving ML
Learn real-world ML model development with a primary focus on data privacy – A practical guide.
Classical ML and Deep Learning
Model Calibration (Part 1)
How to make ML models reflect true probabilities in their predictions?
Engineering Best Practices
A Practical Guide to Scaling ML Model Training
GPUs - GPU Clusters - Distributed Training.
Classical ML and Deep Learning
Conformal Predictions: Build Confidence in Your ML Model's Predictions
A critical step towards building and using ML models reliably.
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.
Engineering Best Practices
How to Structure Your Code for Machine Learning Development
A highly overlooked yet critical skill for data scientists.
