MIT Sloan AI Adoption: Build a Playbook That Drives Real Business ROI
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Master the Weights & Biases machine learning operations platform through this comprehensive tutorial series spanning 2 hours and 37 minutes. Learn to log your first experimental run, integrate W&B with popular frameworks including PyTorch and Keras, and implement version control for both data and models using W&B Artifacts. Discover how to supercharge your training workflows by combining PyTorch Lightning with Weights & Biases, log diverse types of experimental data and metrics, and efficiently tune hyperparameters using W&B Sweeps functionality. Gain hands-on experience with essential MLOps practices including experiment tracking, model versioning, and automated hyperparameter optimization through practical demonstrations led by a Deep Learning Educator with a PhD.
Syllabus
Log Your First Run With W&B
Integrate Weights & Biases with PyTorch
Integrate Weights & Biases with Keras
Version Control Data and Models with W&B Artifacts
âš¡ Supercharge your Training with PyTorch Lightning + Weights & Biases
Log (Almost) Anything with Weights & Biases
Tune Hyperparameters Easily with W&B Sweeps
Taught by
Weights & Biases