Learn to build a neural network using Python and PyTorch in this comprehensive tutorial. Explore real-world weather data to create a model that predicts tomorrow's rainfall. Begin by downloading and preprocessing the dataset, then construct a neural network using PyTorch. Discover how to select appropriate loss functions and optimizers, and leverage GPU acceleration with CUDA. Master the process of training your neural network, saving and loading models, and evaluating their performance. Finally, apply your knowledge to make practical predictions about future rainfall. Gain hands-on experience in deep learning techniques while working with authentic meteorological data.
Build a Neural Network with Python Tutorial - Deep Learning with PyTorch
Overview
Syllabus
Download the weather data
Data preprocessing
Build a Neural Network with PyTorch
Choose a loss function & optimizer
Doing computations on the GPU with CUDA
Training your Neural Network
Saving & loading a model with PyTorch
Evaluation How good your model is?
Making predictions Is it going to rain?
Taught by
Venelin Valkov
