Video that I found useful that covers all the main topics of Deep Learning (in PyTorch) in an introductory but practical way: https://www.youtube.com/watch?v=c36lUUr864M
What is a Tensor: https://pytorch.org/tutorials/beginner/basics/tensorqs_tutorial.html
Building Models with PyTorch: https://pytorch.org/tutorials/beginner/introyt/modelsyt_tutorial.html
Loading Datasets: https://pytorch.org/tutorials/beginner/basics/data_tutorial.html
Gradients: https://pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html
Training: https://pytorch.org/tutorials/beginner/basics/optimization_tutorial.html
Saving and Loading Models: https://pytorch.org/tutorials/beginner/basics/saveloadrun_tutorial.html
1 Introduction to LSTMS: https://towardsdatascience.com/pytorch-lstms-for-time-series-data-cd16190929d7
2 LSTMS (Practical intro): https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/content/courses/deeplearning/notebooks/pytorch/Time_Series_Prediction_with_LSTM_Using_PyTorch.ipynb
3 Video related to Time sequence prediction with LSTM: https://www.youtube.com/watch?v=AvKSPZ7oyVg