24 Videos

A practical PyTorch series covering fundamental concepts and real-world machine learning workflows. Learn core concepts such as tensors, models, batches, epochs, optimizers, DataLoaders, gradients, loss functions, and training loops. Then move into advanced topics including CTC Loss, decoding, Softmax, attention mechanisms, and Transformers. The series also covers ML engineering and MLOps tools such as MLflow, Kubeflow, Docker, Vertex AI, and GKE deployment. With more than 15 videos and more coming, the goal is to understand not only how PyTorch works, but how to build, train, and deploy ML models in production.