PyTorch: Tensor, Dataset and Data Augmentation

Data preparation plays an essential part in tackling machine learning issues. PyTorch is a powerful deep-learning framework provides an array of tools that simplify data loading. Its PyTorch Tensor, Dataset, and Data Augmentation Fundamentals course provides students with a thorough knowledge of the fundamentals and fundamental principles of PyTorch with a particular focus on manipulating tensors, dataset management, and techniques for data augmentation. The course equips you with necessary skills to manage and efficiently transform data to perform machines learning-related tasks. Students will dive into the fundamental elements of using tensors using PyTorch. They will be taught how to effectively manipulate tensors, use mathematical operations using tensor-based functions, and use them to perform tasks such as data preprocessing and modeling training. Through a series of talks and hands-on activities, you will develop a thorough understanding of the capacities for loading data, PyTorch Dataset Object, and discover how to process and enhance data in order to improve the performance of models.