Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch supported computation, CUDA-friendly, and feasible to use as a final loss. I can confirm that you can train a (sequential) model with this as a final loss! The following image shows training logs of a TTS model using the Soft-DTW Loss Function. There are some previous implementations: mblondel’s soft-dtw lyprince’s sdtw_pytorch Maghoumi’s pytorch-softdtw-cuda But they are […]

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch List of Algorithms Covered 📌 Day 1 – Linear Regression 📌 Day 2 – Logistic Regression 📌 Day 3 – Decision Tree 📌 Day 4 – KMeans Clustering 📌 Day 5 – Naive Bayes 📌 Day 6 – K Nearest Neighbour (KNN) 📌 Day 7 – Support Vector Machine 📌 Day 8 – Tf-Idf Model 📌 […]